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You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['tablelamp', 'toilet', 'chair', 'walllamp', 'drawing', 'orchid', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'ceilinglamp', 'mat', 'mousepad', 'closetdrawer', 'wall', 'nightstand', 'powersocket', 'check', 'television', 'wine', 'doorjamb', 'mouse', 'kitchen_counter', 'dresser', 'light', 'table', 'clothes_skirt']
Task:Write an email
response:
{
"thoughts": enter office, find computer, turn it on,,
"actions": ['[WALK] <home_office>', '[WALK] <computer>', '[FIND] <computer>', '[SWITCHON] <computer>', '[FIND] <keyboard>', '[TOUCH] <keyboard>', '[TYPE] <keyboard>']
}
|
Scene_Objects:['sheets', 'toilet', 'freezer', 'walllamp', 'cat', 'drawing', 'orchid', 'floor', 'button', 'bookmark', 'ceilinglamp', 'window', 'couch', 'microphone', 'pillow', 'wall', 'pasta', 'tape', 'box', 'novel', 'curtain', 'doorjamb', 'hairbrush', 'door', 'home_office', 'table', 'bathroom_cabinet', 'soap', 'tooth_paste', 'clothes_shirt']
Task:Text friends while sitting on couch
response:
| {
"thoughts": "Text while sitting",
"actions": [
"[WALK] <home_office>",
"[WALK] <phone>",
"[FIND] <phone>",
"[GRAB] <phone>",
"[WALK] <couch>",
"[SIT] <couch>",
"[TURNTO] <phone>",
"[LOOKAT] <phone>",
"[TOUCH] <phone>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['microwave', 'chair', 'freezer', 'walllamp', 'drawing', 'orchid', 'cpuscreen', 'floor', 'keyboard', 'computer', 'mat', 'tvstand', 'ceilinglamp', 'stereo', 'window', 'couch', 'candle', 'clothes_hat', 'pillow', 'wall', 'oven', 'coffe_maker', 'television', 'curtain', 'diary', 'towel_rack', 'mouse', 'dishrack', 'home_office', 'table']
Task:Relax on sofa
response:
{
"thoughts": I walk to the living room. I see the couch. I sit down on the couch, then lie down and put my feet up.,
"actions": ['[WALK] <home_office>', '[WALK] <couch>', '[FIND] <couch>', '[SIT] <couch>', '[LIE] <couch>']
}
|
Scene_Objects:['sponge', 'food_pizza', 'juice', 'crayon', 'blow_dryer', 'bathroom', 'trashcan', 'drawing', 'cpuscreen', 'bathroom_counter', 'floor', 'ceiling', 'bedroom', 'mat', 'tvstand', 'faucet', 'wall', 'powersocket', 'bench', 'tape', 'photoframe', 'clothes_gloves', 'food_donut', 'after_shave', 'doorjamb', 'dishrack', 'door', 'sink', 'bathroom_cabinet', 'soap']
Task:Clean sink
response:
| {
"thoughts": "Take a premoistened cleaning wipe and wipe down top of sink and faucet. Next clean the sink bowl. Let air dry.",
"actions": [
"[WALK] <bathroom>",
"[WALK] <rag>",
"[FIND] <rag>",
"[GRAB] <rag>",
"[WALK] <sink>",
"[FIND] <faucet>",
"[WIPE] <faucet>",
"[WIPE] <sink>",
"[PUTOBJBACK] <rag>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['food_bread', 'scissors', 'crayon', 'freezer', 'walllamp', 'drawing', 'orchid', 'floor', 'ceiling', 'character', 'bookmark', 'toaster', 'ceilinglamp', 'stovefan', 'faucet', 'window', 'homework', 'couch', 'wall', 'child', 'bench', 'photoframe', 'newspaper', 'coffe_maker', 'razor', 'television', 'kitchen_counter', 'cupboard', 'table', 'coffee']
Task:Let baby learn how to walk
response:
{
"thoughts": The baby tries to stand up and balances on the couch and there are no sharp edges so it's safe.,
"actions": ['[WALK] <home_office>', '[WALK] <child>', '[FIND] <child>', '[TOUCH] <child>', '[GREET] <child>', '[FIND] <couch>', '[TURNTO] <couch>', '[POINTAT] <couch>', '[TURNTO] <child>', '[LOOKAT] <child>']
}
|
Scene_Objects:['food_salt', 'microwave', 'walllamp', 'bathroom', 'trashcan', 'orchid', 'floor', 'ceiling', 'character', 'toaster', 'ceilinglamp', 'tvstand', 'stereo', 'deck_of_cards', 'oil', 'wall', 'bench', 'powersocket', 'novel', 'coffe_maker', 'food_food', 'television', 'tray', 'rag', 'pencil', 'kitchen_counter', 'cupboard', 'sink', 'dishwasher', 'scrabble']
Task:Make popcorn
response:
| {
"thoughts": "Lay popcorn bag flat inside microwave and press popcorn button to start.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <food_food>",
"[FIND] <food_food>",
"[GRAB] <food_food>",
"[WALK] <microwave>",
"[TURNTO] <microwave>",
"[OPEN] <microwave>",
"[PUTIN] <food_food> <microwave>",
"[CLOSE] <microwave>",
"[SWITCHON] <microwave>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'chair', 'walllamp', 'detergent', 'knifeblock', 'orchid', 'cpuscreen', 'drawing', 'bathroom_counter', 'phone', 'folder', 'man', 'keyboard', 'mop_bucket', 'tvstand', 'faucet', 'picture', 'plate', 'mousepad', 'bench', 'oven', 'powersocket', 'photoframe', 'food_food', 'check', 'food_onion', 'clothes_scarf', 'spoon', 'light', 'dishwasher']
Task:Greet guests
response:
{
"thoughts": When someone knocks I n the door walk through the hallway and greet them.,
"actions": ['[RUN] <home_office>', '[WALK] <man>', '[FIND] <man>', '[GREET] <man>', '[FIND] <man>', '[GREET] <man>']
}
|
Scene_Objects:['filing_cabinet', 'chair', 'freezer', 'walllamp', 'food_butter', 'toothbrush', 'knifeblock', 'floor', 'character', 'bookshelf', 'food_cake', 'mat', 'shoe-shine_kit', 'shower', 'mousepad', 'couch', 'microphone', 'cup', 'newspaper', 'mouthwash', 'television', 'coffee_filter', 'food_donut', 'console', 'kitchen_counter', 'headset', 'dresser', 'cupboard', 'clothes_dress', 'home_office']
Task:Answer door
response:
| {
"thoughts": "Wait until doorbell rings, look to see who it is outside and open the door if you feel so inclined.",
"actions": [
"[WALK] <home_office>",
"[WALK] <man>",
"[FIND] <man>",
"[GREET] <man>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['glue', 'sponge', 'scissors', 'chair', 'dog', 'drawing', 'bills', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'phone', 'desk', 'ceilinglamp', 'shoe-shine_kit', 'window', 'foundation', 'couch', 'wall', 'bench', 'basket_for_clothes', 'bed', 'novel', 'television', 'kitchen_counter', 'dresser', 'cupboard', 'bathroom_cabinet', 'light', 'table']
Task:Read book
response:
{
"thoughts": Grab book. Read it.,
"actions": ['[WALK] <home_office>', '[WALK] <dresser>', '[OPEN] <dresser>', '[FIND] <novel>', '[GRAB] <novel>', '[CLOSE] <dresser>', '[FIND] <couch>', '[SIT] <couch>', '[READ] <novel>']
}
|
Scene_Objects:['fork', 'tablelamp', 'microwave', 'jelly', 'walllamp', 'trashcan', 'bathroom_counter', 'floor', 'ceiling', 'character', 'table_cloth', 'toaster', 'stovefan', 'mat', 'iron', 'pillow', 'dining_room', 'wall', 'powersocket', 'cup', 'photoframe', 'coffe_maker', 'television', 'pencil', 'kitchen_counter', 'hairbrush', 'cupboard', 'door', 'dishwasher', 'clothes_skirt']
Task:Make coffee
response:
| {
"thoughts": "Making coffee",
"actions": [
"[WALK] <dining_room>",
"[WALK] <coffe_maker>",
"[FIND] <coffe_maker>",
"[SWITCHON] <coffe_maker>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'scissors', 'beer', 'microwave', 'bathroom', 'drawing', 'hanger', 'floor', 'ceiling', 'character', 'toaster', 'brush', 'plate', 'shower', 'clothes_socks', 'dining_room', 'wall', 'powersocket', 'tape', 'box', 'cup', 'coffe_maker', 'food_food', 'doorjamb', 'centerpiece', 'mouse', 'pencil', 'kitchen_counter', 'cupboard', 'dishwasher']
Task:Wash dishes with dishwasher
response:
{
"thoughts": In the kitchen, open up the dishwasher. Take plates from the sink and put them in the dishwasher one by one. Close the dishwasher. Program it. Push start.,
"actions": ['[WALK] <dining_room>', '[WALK] <dishwasher>', '[FIND] <dishwasher>', '[OPEN] <dishwasher>', '[FIND] <plate>', '[GRAB] <plate>', '[PUTBACK] <plate> <dishwasher>', '[FIND] <plate>', '[GRAB] <plate>', '[PUTBACK] <plate> <dishwasher>', '[FIND] <plate>', '[GRAB] <plate>', '[PUTBACK] <plate> <dishwasher>', '[CLOSE] <dishwasher>', '[SWITCHON] <dishwasher>']
}
|
Scene_Objects:['beer', 'walllamp', 'drawing', 'orchid', 'food_egg', 'hanger', 'floor', 'ceiling', 'phone', 'desk', 'remote_control', 'toaster', 'ceilinglamp', 'tvstand', 'mat', 'faucet', 'window', 'couch', 'candle', 'pillow', 'wall', 'nightstand', 'powersocket', 'keys', 'television', 'curtain', 'doorjamb', 'door', 'sink', 'table']
Task:Watch movie
response:
| {
"thoughts": "Sit down on couch in front of TV. Use remote to turn on the TV",
"actions": [
"[WALK] <home_office>",
"[WALK] <couch>",
"[FIND] <couch>",
"[SIT] <couch>",
"[FIND] <remote_control>",
"[GRAB] <remote_control>",
"[FIND] <television>",
"[SWITCHON] <television>",
"[TURNTO] <television>",
"[WATCH] <television>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'food_pizza', 'ground_coffee', 'walllamp', 'food_carrot', 'knifeblock', 'floor', 'ceiling', 'character', 'computer', 'piano_bench', 'stovefan', 'toaster', 'tvstand', 'faucet', 'oil', 'pillow', 'wall', 'oven', 'powersocket', 'food_food', 'water', 'tray', 'after_shave', 'doorjamb', 'kitchen_counter', 'dresser', 'cupboard', 'door', 'dishwasher']
Task:Make coffee
response:
{
"thoughts": Get my coffee pot going,
"actions": ['[WALK] <dining_room>', '[WALK] <coffee_pot>', '[FIND] <coffee_pot>', '[GRAB] <coffee_pot>', '[WALK] <water>', '[FIND] <water>', '[GRAB] <water>', '[POUR] <water> <coffee_pot>', '[FIND] <ground_coffee>', '[GRAB] <ground_coffee>', '[PUTBACK] <ground_coffee> <coffee_pot>', '[GRAB] <ground_coffee>', '[PUTOBJBACK] <ground_coffee>', '[WALK] <oven>', '[PUTBACK] <coffee_pot> <oven>', '[SWITCHON] <oven>']
}
|
Scene_Objects:['pot', 'filing_cabinet', 'jelly', 'freezer', 'walllamp', 'ground_coffee', 'knife', 'knifeblock', 'cpuscreen', 'orchid', 'needle', 'floor', 'ceiling', 'desk', 'stovefan', 'ceilinglamp', 'faucet', 'mousepad', 'clothes_hat', 'wall', 'oven', 'cup', 'food_food', 'toothbrush_holder', 'tray', 'rag', 'kitchen_counter', 'cupboard', 'sink', 'bag']
Task:Clean
response:
| {
"thoughts": "Take out a rag. Turn on faucet and get water on the rag. Clean counter off.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <rag>",
"[FIND] <rag>",
"[GRAB] <rag>",
"[WALK] <sink>",
"[FIND] <faucet>",
"[SWITCHON] <faucet>",
"[PUTBACK] <rag> <sink>",
"[SWITCHOFF] <faucet>",
"[GRAB] <rag>",
"[SQUEEZE] <rag>",
"[WALK] <kitchen_counter>",
"[WIPE] <kitchen_counter>",
"[PUTOBJBACK] <rag>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'pot', 'food_pizza', 'food_salt', 'freezer', 'drawing', 'knife', 'cpuscreen', 'knifeblock', 'floor', 'character', 'bookshelf', 'laptop', 'plate', 'mousepad', 'candle', 'dining_room', 'wall', 'light_bulb', 'food_food', 'coffe_maker', 'tray', 'kitchen_counter', 'chessboard', 'dishrack', 'shoes', 'cupboard', 'laundry_detergent', 'dishwasher', 'instrument_violin']
Task:Wash dishes with dishwasher
response:
{
"thoughts": I walk to the kitchen. I take plate. I open the dishwasher. I put plate in the dishwasher. I switch on the dishwasher.,
"actions": ['[WALK] <dining_room>', '[WALK] <plate>', '[FIND] <plate>', '[GRAB] <plate>', '[WALK] <dishwasher>', '[OPEN] <dishwasher>', '[PUTBACK] <plate> <dishwasher>', '[CLOSE] <dishwasher>', '[SWITCHON] <dishwasher>']
}
|
Scene_Objects:['tablelamp', 'measuring_cup', 'walllamp', 'trashcan', 'drawing', 'bathroom_counter', 'floor', 'ceiling', 'phone', 'face', 'computer', 'bookmark', 'mat', 'faucet', 'mousepad', 'clothes_hat', 'towel', 'dining_room', 'wall', 'wall_clock', 'nightstand', 'face_soap', 'basket_for_clothes', 'newspaper', 'tray', 'rag', 'mouse', 'dishrack', 'sink', 'bathroom_cabinet']
Task:Wash face
response:
| {
"thoughts": "Turn on water faucet. Get rag wet. Get face soap out. Squirt face soap in hands and put it on face. Rub soap into face. Wash soap off of face. Dry face off on the hand towel. Hang out rag and hand towel.",
"actions": [
"[WALK] <bathroom>",
"[WALK] <sink>",
"[FIND] <rag>",
"[GRAB] <rag>",
"[FIND] <faucet>",
"[SWITCHON] <faucet>",
"[WASH] <rag>",
"[FIND] <face_soap>",
"[GRAB] <face_soap>",
"[POUR] <face_soap> <rag>",
"[PUTOBJBACK] <face_soap>",
"[FIND] <face>",
"[SCRUB] <face>",
"[PUTBACK] <rag> <sink>",
"[RINSE] <face>",
"[RINSE] <rag>",
"[SWITCHOFF] <faucet>",
"[GRAB] <rag>",
"[PUTOBJBACK] <rag>",
"[FIND] <towel>",
"[GRAB] <towel>",
"[WIPE] <face>",
"[PUTOBJBACK] <towel>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'detergent', 'drawing', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'dvd_player', 'folder', 'desk', 'bookshelf', 'keyboard', 'computer', 'mat', 'tvstand', 'shower', 'homework', 'oil', 'dustpan', 'dining_room', 'wall', 'powersocket', 'bench', 'curtain', 'doorjamb', 'towel_rack', 'mouse', 'door', 'home_office', 'light']
Task:Turn on light
response:
{
"thoughts": Walk into the bedroom and walk to the light switch. Flip the switch.,
"actions": ['[WALK] <bedroom>', '[WALK] <light>', '[FIND] <light>', '[SWITCHON] <light>']
}
|
Scene_Objects:['fork', 'pot', 'tablelamp', 'microwave', 'dog', 'walllamp', 'trashcan', 'knifeblock', 'knife', 'kitchen_cabinet', 'floor', 'ceiling', 'toaster', 'stovefan', 'plate', 'faucet', 'ceilinglamp', 'oil', 'wall', 'oven', 'coffe_maker', 'drinking_glass', 'tray', 'kitchen_counter', 'cupboard', 'sink', 'spoon', 'bag', 'dishwasher', 'colander']
Task:Unload dishwasher
response:
| {
"thoughts": "Open the dishwasher door. Take out all of the dishes and silverware. Put the dishes and silverware in their drawers and cabinets. Close the dishwasher door.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <dishwasher>",
"[FIND] <dishwasher>",
"[OPEN] <dishwasher>",
"[FIND] <drinking_glass>",
"[GRAB] <drinking_glass>",
"[FIND] <cupboard>",
"[OPEN] <cupboard>",
"[PUTBACK] <drinking_glass> <cupboard>",
"[FIND] <fork>",
"[GRAB] <fork>",
"[FIND] <kitchen_cabinet>",
"[OPEN] <kitchen_cabinet>",
"[PUTIN] <fork> <kitchen_cabinet>",
"[FIND] <knife>",
"[GRAB] <knife>",
"[PUTIN] <knife> <kitchen_cabinet>",
"[FIND] <spoon>",
"[GRAB] <spoon>",
"[PUTIN] <spoon> <kitchen_cabinet>",
"[FIND] <plate>",
"[GRAB] <plate>",
"[PUTIN] <plate> <kitchen_cabinet>",
"[CLOSE] <kitchen_cabinet>",
"[CLOSE] <dishwasher>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'filing_cabinet', 'microwave', 'walllamp', 'drawing', 'knifeblock', 'wallshelf', 'floor', 'ceiling', 'phone', 'keyboard', 'computer', 'stovefan', 'plate', 'faucet', 'tvstand', 'window', 'dish_soap', 'towel', 'dining_room', 'wall', 'wall_clock', 'oven', 'coffe_maker', 'food_food', 'curtain', 'kitchen_counter', 'cupboard', 'food_steak', 'sink']
Task:Wash dishes by hand
response:
{
"thoughts": Walk to Kitchen, find sink, find dishes and dish soap. Put soap on plate. open faucet, rinse dishes close faucet.,
"actions": ['[WALK] <dining_room>', '[WALK] <sink>', '[FIND] <sink>', '[FIND] <plate>', '[GRAB] <plate>', '[FIND] <dish_soap>', '[GRAB] <dish_soap>', '[PUTBACK] <dish_soap> <plate>', '[FIND] <faucet>', '[SWITCHON] <faucet>', '[RINSE] <plate>']
}
|
Scene_Objects:['chair', 'walllamp', 'cat', 'orchid', 'cpuscreen', 'bathroom_counter', 'floor', 'ceiling', 'desk', 'bedroom', 'keyboard', 'computer', 'bookmark', 'mat', 'ceilinglamp', 'food_noodles', 'mousepad', 'wall', 'oven', 'check', 'video_game_controller', 'television', 'oven_mitts', 'after_shave', 'food_onion', 'centerpiece', 'mouse', 'door', 'table', 'coffee']
Task:Use computer
response:
| {
"thoughts": "Sit at my desk and grade papers on my computer",
"actions": [
"[WALK] <home_office>",
"[WALK] <chair>",
"[FIND] <chair>",
"[SIT] <chair>",
"[FIND] <computer>",
"[SWITCHON] <computer>",
"[TURNTO] <computer>",
"[LOOKAT] <computer>",
"[FIND] <keyboard>",
"[TYPE] <keyboard>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'jelly', 'freezer', 'food_carrot', 'drawing', 'floor', 'ceiling', 'desk', 'envelope', 'table_cloth', 'mat', 'faucet', 'mousepad', 'couch', 'pillow', 'towel', 'wall', 'cup', 'food_food', 'mouthwash', 'television', 'water', 'tray', 'curtain', 'kitchen_counter', 'cupboard', 'food_steak', 'light', 'dishwasher', 'table']
Task:Drink
response:
{
"thoughts": Walk into kitchen, look for cup, walk to cup, look for refrigerator, walk to refrigerator, open door, grab water, pour water into cup,
"actions": ['[WALK] <dining_room>', '[WALK] <cup>', '[FIND] <cup>', '[TURNTO] <cup>', '[LOOKAT] <cup>', '[WALK] <cup>', '[FIND] <freezer>', '[TURNTO] <freezer>', '[LOOKAT] <freezer>', '[WALK] <freezer>', '[GRAB] <cup>', '[WALK] <water>', '[FIND] <water>', '[GRAB] <water>', '[POUR] <water> <cup>']
}
|
Scene_Objects:['food_carrot', 'milk', 'dough', 'knifeblock', 'drawing', 'bathroom_counter', 'floor', 'ceiling', 'desk', 'bedroom', 'mat', 'faucet', 'shower', 'stereo', 'towel', 'pillow', 'wall', 'bench', 'cup', 'bed', 'photoframe', 'coffe_maker', 'wooden_spoon', 'after_shave', 'rag', 'mouse', 'sink', 'bathroom_cabinet', 'soap', 'hands_both']
Task:Wash hands
response:
| {
"thoughts": "Turn on the water faucet. Wet my hands and turn off the faucet. Put soap on my hands. Rub hands together, making sure the soap covers all areas of the hands. Scrub hands for about 20 seconds. Turn on the water water faucet. Rinse hands under the running water. Turn off the water faucet. Dry hands with a towel.",
"actions": [
"[WALK] <bathroom>",
"[WALK] <sink>",
"[FIND] <sink>",
"[TURNTO] <sink>",
"[FIND] <faucet>",
"[SWITCHON] <faucet>",
"[FIND] <hands_both>",
"[WASH] <hands_both>",
"[FIND] <soap>",
"[GRAB] <soap>",
"[SCRUB] <hands_both>",
"[PUTOBJBACK] <soap>",
"[RINSE] <hands_both>",
"[SWITCHOFF] <faucet>",
"[FIND] <towel>",
"[GRAB] <towel>",
"[WIPE] <hands_both>",
"[PUTOBJBACK] <towel>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['food_ice_cream', 'microwave', 'toilet', 'chair', 'knifeblock', 'hanger', 'floor', 'toaster', 'stovefan', 'shoe-shine_kit', 'faucet', 'homework', 'food_noodles', 'mousepad', 'couch', 'wall', 'nightstand', 'powersocket', 'cup', 'newspaper', 'coffee_filter', 'food_rice', 'console', 'mouse', 'kitchen_counter', 'dishrack', 'comb', 'cupboard', 'door', 'sink']
Task:Drink
response:
{
"thoughts": go to the kitchen, walk to the cabinet, pic up a glass. carry the glass to the sink. turn on the water and fill up the glass. drink the water.,
"actions": ['[WALK] <dining_room>', '[WALK] <sink>', '[FIND] <cup>', '[GRAB] <cup>', '[WALK] <water>', '[FIND] <water>', '[GRAB] <water>', '[POUR] <water> <cup>', '[DRINK] <cup>']
}
|
Scene_Objects:['mop', 'freezer', 'trashcan', 'milk', 'knifeblock', 'orchid', 'clothes_underwear', 'bookshelf', 'purse', 'thread', 'computer', 'ceilinglamp', 'tvstand', 'iron', 'couch', 'microphone', 'wall', 'cutting_board', 'basket_for_clothes', 'keys', 'toothbrush_holder', 'oven_mitts', 'curtain', 'doorjamb', 'diary', 'chessboard', 'home_office', 'bathroom_cabinet', 'clothes_skirt', 'light']
Task:Hang up car keys
response:
| {
"thoughts": "Open the front door. Enter the entrance hall. Take out car keys from purse. Hang car keys up on hook on the wall.",
"actions": [
"[WALK] <home_office>",
"[WALK] <purse>",
"[FIND] <purse>",
"[OPEN] <purse>",
"[FIND] <keys>",
"[GRAB] <keys>",
"[CLOSE] <purse>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['microwave', 'chair', 'drawing', 'hanger', 'floor', 'phone', 'ceilinglamp', 'plate', 'iron', 'candle', 'pillow', 'wall', 'bench', 'powersocket', 'oven', 'food_food', 'video_game_controller', 'check', 'wooden_spoon', 'after_shave', 'doorjamb', 'shoes', 'dresser', 'cupboard', 'clothes_dress', 'door', 'conditioner', 'sink', 'table', 'light']
Task:Eat dinner
response:
{
"thoughts": Put food on the table, sit down, and eat the food.,
"actions": ['[WALK] <dining_room>', '[WALK] <plate>', '[FIND] <plate>', '[GRAB] <plate>', '[FIND] <food_food>', '[GRAB] <food_food>', '[PUTBACK] <food_food> <plate>', '[WALK] <dining_room>', '[WALK] <table>', '[FIND] <table>', '[PUTBACK] <plate> <table>', '[FIND] <chair>', '[SIT] <chair>', '[EAT] <plate>']
}
|
Scene_Objects:['walllamp', 'food_carrot', 'drawing', 'orchid', 'knifeblock', 'cpuscreen', 'floor', 'ceiling', 'bedroom', 'stovefan', 'mat', 'tvstand', 'ceilinglamp', 'couch', 'microphone', 'pillow', 'wall', 'wall_clock', 'photoframe', 'television', 'toothbrush_holder', 'food_donut', 'doorjamb', 'shaving_cream', 'mouse', 'door', 'sink', 'clothes_scarf', 'napkin', 'table']
Task:Straighten pictures on wall
response:
| {
"thoughts": "Move the pictures/paintings until they are straight.",
"actions": [
"[WALK] <home_office>",
"[WALK] <drawing>",
"[FIND] <drawing>",
"[TURNTO] <drawing>",
"[LOOKAT] <drawing>",
"[TOUCH] <drawing>",
"[PUSH] <drawing>",
"[FIND] <drawing>",
"[TURNTO] <drawing>",
"[LOOKAT] <drawing>",
"[TOUCH] <drawing>",
"[PUSH] <drawing>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'pot', 'food_pizza', 'dry_pasta', 'walllamp', 'trashcan', 'food_carrot', 'dough', 'knifeblock', 'orchid', 'bathroom_counter', 'floor', 'ceiling', 'table_cloth', 'stovefan', 'toaster', 'wall', 'wall_clock', 'oven', 'food_cheese', 'food_food', 'coffe_maker', 'tray', 'doorjamb', 'coffee_pot', 'kitchen_counter', 'cupboard', 'home_office', 'table', 'dishwasher']
Task:Keep an eye on stove as something is cooking
response:
{
"thoughts": Watch whatever is cooking on the stove so it doesn't burn or pour. Turn off heat when done,
"actions": ['[WALK] <dining_room>', '[WALK] <oven>', '[FIND] <pot>', '[TURNTO] <pot>', '[LOOKAT] <pot>', '[FIND] <wall_clock>', '[TURNTO] <wall_clock>', '[LOOKAT] <wall_clock>', '[SWITCHOFF] <oven>']
}
|
Scene_Objects:['food_ice_cream', 'measuring_cup', 'freezer', 'nail_polish', 'food_carrot', 'drawing', 'cpuscreen', 'kitchen_cabinet', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'ceilinglamp', 'plate', 'mat', 'mousepad', 'food_peanut_butter', 'pillow', 'wall', 'powersocket', 'bench', 'food_vegetable', 'food_food', 'doorjamb', 'mouse', 'door', 'light', 'table', 'scrabble']
Task:Fix snack
response:
| {
"thoughts": "Open fridge. Take out carrots and other vegetables. Put vegetables on a plate. Put away carrots and celery. Close fridge.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <kitchen_cabinet>",
"[FIND] <kitchen_cabinet>",
"[OPEN] <kitchen_cabinet>",
"[FIND] <plate>",
"[GRAB] <plate>",
"[CLOSE] <kitchen_cabinet>",
"[WALK] <freezer>",
"[OPEN] <freezer>",
"[FIND] <food_carrot>",
"[GRAB] <food_carrot>",
"[PUTBACK] <food_carrot> <plate>",
"[FIND] <food_vegetable>",
"[GRAB] <food_vegetable>",
"[PUTBACK] <food_vegetable> <plate>",
"[CLOSE] <freezer>",
"[WALK] <table>",
"[PUTBACK] <plate> <table>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'filing_cabinet', 'food_salt', 'measuring_cup', 'toilet', 'jelly', 'drawing', 'floor', 'phone', 'ceiling', 'character', 'bookshelf', 'alcohol', 'mat', 'shower', 'foundation', 'electric_shaver', 'mousepad', 'wall', 'toy', 'basket_for_clothes', 'photoframe', 'wine', 'dresser', 'laundry_detergent', 'food_steak', 'door', 'napkin', 'bathroom_cabinet', 'dishwasher']
Task:Pick up toys
response:
{
"thoughts": Pickup toys from around the room. Organize toys back into their appropriate spaces on the shelves and into the toy boxes.,
"actions": ['[WALK] <bedroom>', '[WALK] <toy>', '[FIND] <toy>', '[GRAB] <toy>', '[WALK] <filing_cabinet>', '[OPEN] <filing_cabinet>', '[PUTBACK] <toy> <filing_cabinet>', '[CLOSE] <filing_cabinet>', '[FIND] <toy>', '[GRAB] <toy>', '[WALK] <dresser>', '[OPEN] <dresser>', '[PUTBACK] <toy> <dresser>', '[CLOSE] <dresser>', '[FIND] <toy>', '[GRAB] <toy>', '[WALK] <filing_cabinet>', '[OPEN] <filing_cabinet>', '[PUTBACK] <toy> <filing_cabinet>', '[CLOSE] <filing_cabinet>']
}
|
Scene_Objects:['dry_pasta', 'sheets', 'pot', 'freezer', 'cpuscreen', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'mail', 'tvstand', 'stereo', 'window', 'mousepad', 'clothes_socks', 'wall', 'nightstand', 'powersocket', 'pasta', 'oven', 'light_bulb', 'coffe_maker', 'food_rice', 'doorjamb', 'shaving_cream', 'mouse', 'kitchen_counter', 'door', 'light']
Task:Turn light off
response:
| {
"thoughts": "Put the light switch into the down, or off, position.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <light>",
"[FIND] <light>",
"[SWITCHOFF] <light>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['juice', 'toilet', 'chair', 'freezer', 'detergent', 'food_carrot', 'drawing', 'knifeblock', 'floor', 'ceiling', 'food_chicken', 'bedroom', 'piano_bench', 'ceilinglamp', 'mat', 'shower', 'faucet', 'oil', 'food_orange', 'wall', 'nightstand', 'powersocket', 'photoframe', 'food_food', 'check', 'doorjamb', 'vacuum_cleaner', 'door', 'table', 'light']
Task:Put groceries in Fridge
response:
{
"thoughts": Put the groceries on the table into the fridge,
"actions": ['[WALK] <dining_room>', '[WALK] <table>', '[FIND] <food_chicken>', '[GRAB] <food_chicken>', '[FIND] <freezer>', '[OPEN] <freezer>', '[PUTBACK] <food_chicken> <freezer>', '[CLOSE] <freezer>', '[FIND] <food_carrot>', '[GRAB] <food_carrot>', '[FIND] <freezer>', '[OPEN] <freezer>', '[PUTIN] <food_carrot> <freezer>', '[CLOSE] <freezer>']
}
|
Scene_Objects:['tablelamp', 'walllamp', 'dough', 'drawing', 'orchid', 'needle', 'floor', 'ceiling', 'desk', 'bookshelf', 'computer', 'bookmark', 'stovefan', 'mat', 'tvstand', 'ceilinglamp', 'couch', 'pillow', 'food_kiwi', 'wall', 'oven', 'photoframe', 'novel', 'television', 'doorjamb', 'mouse', 'dresser', 'door', 'home_office', 'table']
Task:Admire art
response:
| {
"thoughts": "Looking at painting, art",
"actions": [
"[WALK] <home_office>",
"[WALK] <drawing>",
"[TURNTO] <drawing>",
"[LOOKAT] <drawing>",
"[FIND] <drawing>",
"[TURNTO] <drawing>",
"[LOOKAT] <drawing>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['tea', 'microwave', 'toilet', 'jelly', 'bathroom_counter', 'floor', 'ceiling', 'toaster', 'mat', 'faucet', 'food_noodles', 'clothes_socks', 'mousepad', 'closetdrawer', 'food_kiwi', 'wall', 'cutting_board', 'cup', 'coffe_maker', 'toothbrush_holder', 'television', 'oven_mitts', 'water', 'kitchen_counter', 'dresser', 'cupboard', 'sink', 'home_office', 'soap', 'tooth_paste']
Task:Drink
response:
{
"thoughts": Walk to kitchen, walk to cupboard, open cupboard, grab cup, walk to sink, pour water in cup, drink water.,
"actions": ['[WALK] <dining_room>', '[WALK] <cupboard>', '[FIND] <cupboard>', '[OPEN] <cupboard>', '[FIND] <cup>', '[GRAB] <cup>', '[WALK] <sink>', '[WALK] <water>', '[FIND] <water>', '[GRAB] <water>', '[POUR] <water> <cup>', '[DRINK] <cup>']
}
|
Scene_Objects:['tablelamp', 'chair', 'dough', 'drawing', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'dvd_player', 'desk', 'keyboard', 'bookshelf', 'computer', 'clothes_jacket', 'homework', 'mousepad', 'towel', 'wall', 'nightstand', 'bed', 'novel', 'coffe_maker', 'toothbrush_holder', 'ice', 'diary', 'kettle', 'mouse', 'door', 'spoon', 'instrument_violin']
Task:Study
response:
| {
"thoughts": "Do homework or read books while sitting on the chair.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <chair>",
"[FIND] <chair>",
"[SIT] <chair>",
"[FIND] <novel>",
"[GRAB] <novel>",
"[READ] <novel>",
"[PUTOBJBACK] <novel>",
"[FIND] <novel>",
"[GRAB] <novel>",
"[READ] <novel>",
"[PUTOBJBACK] <novel>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['measuring_cup', 'chair', 'trashcan', 'drawing', 'orchid', 'cpuscreen', 'longboard', 'floor', 'ceiling', 'desk', 'keyboard', 'bookshelf', 'computer', 'ceilinglamp', 'mat', 'window', 'mousepad', 'couch', 'wall', 'powersocket', 'bed', 'curtain', 'doorjamb', 'shaving_cream', 'mouse', 'comb', 'door', 'napkin', 'table', 'light']
Task:Browse internet
response:
{
"thoughts": I turn on computer. I use keyboard to type. I open browser. I search.,
"actions": ['[WALK] <bedroom>', '[WALK] <computer>', '[FIND] <keyboard>', '[TYPE] <keyboard>', '[TURNTO] <computer>', '[LOOKAT] <computer>']
}
|
Scene_Objects:['microwave', 'walllamp', 'drawing', 'orchid', 'hanger', 'floor', 'ceiling', 'video_game_console', 'button', 'toaster', 'ceilinglamp', 'tvstand', 'mat', 'faucet', 'window', 'candle', 'broom', 'wall', 'powersocket', 'check', 'video_game_controller', 'television', 'rag', 'doorjamb', 'kitchen_counter', 'hairbrush', 'door', 'table', 'dishwasher', 'dirt']
Task:Play games
response:
| {
"thoughts": "Turn on the television. Turn on the video game system. Insert desired game into gaming system. Follow directions on game to and push needed buttons on video game remote controller.",
"actions": [
"[WALK] <home_office>",
"[WALK] <television>",
"[FIND] <television>",
"[SWITCHON] <television>",
"[FIND] <video_game_console>",
"[SWITCHON] <video_game_console>",
"[FIND] <video_game_controller>",
"[GRAB] <video_game_controller>",
"[FIND] <button>",
"[PUSH] <button>",
"[TURNTO] <television>",
"[WATCH] <television>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'filing_cabinet', 'food_salt', 'chair', 'bathroom', 'drawing', 'food_egg', 'floor', 'desk', 'bookshelf', 'computer', 'mat', 'stereo', 'shower', 'couch', 'food_peanut_butter', 'wall', 'powersocket', 'oven', 'cup', 'doorjamb', 'mouse', 'kitchen_counter', 'pajamas', 'controller', 'door', 'clothes_scarf', 'light', 'dishwasher', 'board_game']
Task:Pull up carpet
response:
{
"thoughts": Pry up a corner of your old dirty carpet. Tug as hard as you can until it comes off the tacs. Pull up the pad. Try not to be sick at all the dirt.,
"actions": ['[WALK] <home_office>', '[WALK] <mat>', '[FIND] <mat>', '[TOUCH] <mat>', '[PULL] <mat>']
}
|
Scene_Objects:['sheets', 'microwave', 'toilet', 'chair', 'band-aids', 'cat', 'food_carrot', 'knife', 'foundation', 'electric_shaver', 'mousepad', 'clothes_socks', 'pillow', 'dining_room', 'nightstand', 'oven', 'toy', 'check', 'coffe_maker', 'television', 'curtain', 'doorjamb', 'kitchen_counter', 'chessboard', 'cupboard', 'conditioner', 'door', 'food_steak', 'clothes_skirt', 'duster']
Task:Dust
response:
| {
"thoughts": "Get a broom or duster with long handle. Dust blades of ceiling fan.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <duster>",
"[FIND] <duster>",
"[GRAB] <duster>",
"[PUTOBJBACK] <duster>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['tablelamp', 'toilet', 'walllamp', 'orchid', 'knifeblock', 'wallshelf', 'floor', 'ceiling', 'character', 'video_game_console', 'bedroom', 'computer', 'button', 'table_cloth', 'tvstand', 'window', 'closetdrawer', 'couch', 'pillow', 'nightstand', 'wall', 'powersocket', 'box', 'video_game_controller', 'television', 'curtain', 'pencil', 'dresser', 'door', 'table']
Task:Play games
response:
{
"thoughts": Turn on the television. Turn on the video game system. Insert desired game into gaming system. Follow directions on game to and push needed buttons on video game remote controller.,
"actions": ['[WALK] <home_office>', '[WALK] <television>', '[FIND] <television>', '[SWITCHON] <television>', '[FIND] <video_game_console>', '[SWITCHON] <video_game_console>', '[FIND] <video_game_controller>', '[GRAB] <video_game_controller>', '[FIND] <button>', '[PUSH] <button>', '[TURNTO] <television>', '[WATCH] <television>']
}
|
Scene_Objects:['sheets', 'blender', 'toilet', 'walllamp', 'cat', 'drawing', 'orchid', 'floor', 'ceiling', 'bedroom', 'toaster', 'ceilinglamp', 'tvstand', 'mat', 'window', 'couch', 'pillow', 'wall', 'powersocket', 'toy', 'cup', 'bed', 'keys', 'television', 'curtain', 'doorjamb', 'shaving_cream', 'door', 'table', 'shoe_rack']
Task:Watch TV
response:
| {
"thoughts": "Sit on my couch directly opposite my tv , switch on my tv with the remote control and watch",
"actions": [
"[WALK] <home_office>",
"[WALK] <remote_control>",
"[FIND] <remote_control>",
"[GRAB] <remote_control>",
"[WALK] <couch>",
"[SIT] <couch>",
"[TOUCH] <remote_control>",
"[FIND] <television>",
"[SWITCHON] <television>",
"[TURNTO] <television>",
"[WATCH] <television>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'glue', 'tablelamp', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'phone', 'desk', 'keyboard', 'purse', 'computer', 'clothes_jacket', 'toaster', 'stereo', 'mousepad', 'closetdrawer', 'couch', 'wall', 'wall_clock', 'powersocket', 'nightstand', 'bed', 'novel', 'mouse', 'shoes', 'dresser', 'clothes_dress', 'light', 'table']
Task:Get ready for day
response:
{
"thoughts": Grab shoes, purse etc and head out the door!,
"actions": ['[WALK] <bedroom>', '[WALK] <dresser>', '[FIND] <dresser>', '[OPEN] <dresser>', '[FIND] <clothes_dress>', '[GRAB] <clothes_dress>', '[PUTON] <clothes_dress>', '[FIND] <shoes>', '[GRAB] <shoes>', '[PUTON] <shoes>', '[FIND] <purse>', '[GRAB] <purse>', '[CLOSE] <dresser>', '[WALK] <home_office>']
}
|
Scene_Objects:['pot', 'tablelamp', 'drawing', 'needle', 'knife', 'clothes_underwear', 'hanger', 'floor', 'envelope', 'computer', 'ceilinglamp', 'oil', 'mousepad', 'pillow', 'bowl', 'wall', 'nightstand', 'child', 'bed', 'novel', 'food_food', 'coffe_maker', 'television', 'doorjamb', 'dishrack', 'comb', 'laundry_detergent', 'conditioner', 'sink', 'instrument_violin']
Task:Story reading time
response:
| {
"thoughts": "Sit on bed with child, open mother goose, pick story, read book, point at the pretty pictures",
"actions": [
"[WALK] <bedroom>",
"[WALK] <child>",
"[FIND] <child>",
"[GREET] <child>",
"[FIND] <novel>",
"[GRAB] <novel>",
"[FIND] <bed>",
"[SIT] <bed>",
"[TURNTO] <child>",
"[LOOKAT] <child>",
"[TURNTO] <novel>",
"[POINTAT] <novel>",
"[READ] <novel>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['toilet', 'chair', 'walllamp', 'bathroom', 'wallshelf', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'phone', 'desk', 'keyboard', 'envelope', 'computer', 'mop_bucket', 'stovefan', 'mat', 'tvstand', 'toaster', 'foundation', 'mousepad', 'pillow', 'wall', 'standingmirror', 'photoframe', 'toilet_paper', 'oven_mitts', 'tray', 'mouse', 'sink']
Task:Read book
response:
{
"thoughts": go to living room,find the text book on the self ,sat on the chair ,open and read the book,
"actions": ['[WALK] <home_office>', '[WALK] <novel>', '[FIND] <novel>', '[GRAB] <novel>', '[WALK] <home_office>', '[WALK] <chair>', '[FIND] <chair>', '[SIT] <chair>', '[READ] <novel>']
}
|
Scene_Objects:['sponge', 'pot', 'filing_cabinet', 'microwave', 'walllamp', 'drawing', 'orchid', 'bathroom_counter', 'floor', 'ceiling', 'keyboard', 'computer', 'piano_bench', 'mat', 'tvstand', 'faucet', 'shower', 'homework', 'clothes_socks', 'broom', 'wall', 'bench', 'cup', 'rag', 'kitchen_counter', 'laundry_detergent', 'door', 'sink', 'bathroom_cabinet', 'tooth_paste']
Task:Wipe down sink
response:
| {
"thoughts": "Use a cloth to wipe the edge of the sink. Then wipe the bowl of the sink as well.",
"actions": [
"[WALK] <bathroom>",
"[WALK] <bathroom_cabinet>",
"[OPEN] <bathroom_cabinet>",
"[FIND] <rag>",
"[GRAB] <rag>",
"[WALK] <sink>",
"[WIPE] <sink>",
"[PUTOBJBACK] <rag>",
"[CLOSE] <bathroom_cabinet>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sponge', 'spectacles', 'pot', 'microwave', 'knifeblock', 'floor', 'ceiling', 'folder', 'character', 'toaster', 'plate', 'drying_rack', 'faucet', 'dish_soap', 'couch', 'wall', 'powersocket', 'food_cheese', 'photoframe', 'bed', 'food_food', 'mouse', 'kitchen_counter', 'cupboard', 'door', 'sink', 'hairdryer', 'light', 'dirt', 'coffee']
Task:Wash dishes by hand
response:
{
"thoughts": I walk in to the Kitchen. I find a plate, a sponge, and the dish soap. I find the faucet. I turn the faucet on. I pour water on the sponge and plate. I add dish soap to the sponge. I put the dish soap back. I scrub the plate. I rinse the plate. I place the plate on the drying rack. I rinse the sponge. I turn the faucet off.,
"actions": ['[WALK] <dining_room>', '[WALK] <faucet>', '[FIND] <faucet>', '[SWITCHON] <faucet>', '[FIND] <sponge>', '[GRAB] <sponge>', '[RINSE] <sponge>', '[FIND] <dish_soap>', '[GRAB] <dish_soap>', '[POUR] <dish_soap> <sponge>', '[PUTOBJBACK] <dish_soap>', '[FIND] <plate>', '[GRAB] <plate>', '[WASH] <plate>', '[RINSE] <plate>', '[FIND] <drying_rack>', '[PUTBACK] <plate> <plate>', '[RINSE] <sponge>', '[PUTOBJBACK] <sponge>', '[SWITCHOFF] <faucet>']
}
|
Scene_Objects:['glue', 'microwave', 'freezer', 'walllamp', 'drawing', 'hanger', 'floor', 'ceiling', 'bookshelf', 'purse', 'mail', 'ceilinglamp', 'window', 'mousepad', 'couch', 'pillow', 'wall', 'bed', 'light_bulb', 'check', 'food_food', 'curtain', 'kitchen_counter', 'chessboard', 'dishrack', 'dresser', 'laundry_detergent', 'door', 'light', 'shoe_rack']
Task:Open window
response:
| {
"thoughts": "Unlock the latch at the top. Push the bottom half of the window upwards.",
"actions": [
"[WALK] <home_office>",
"[WALK] <window>",
"[OPEN] <window>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['scissors', 'dog', 'walllamp', 'clothes_underwear', 'bathroom_counter', 'phone', 'character', 'desk', 'tea_bag', 'envelope', 'toaster', 'ceilinglamp', 'window', 'mousepad', 'food_kiwi', 'nightstand', 'cutting_board', 'photoframe', 'coffe_maker', 'television', 'tray', 'rag', 'doorjamb', 'diary', 'cupboard', 'hairdryer', 'home_office', 'light', 'table', 'creditcard']
Task:Receive credit card
response:
{
"thoughts": hear the dooble, go to door, take de envelope, open it with a scissor, take the creditcard,
"actions": ['[WALK] <home_office>', '[WALK] <envelope>', '[FIND] <envelope>', '[GRAB] <envelope>', '[WALK] <home_office>', '[WALK] <scissors>', '[FIND] <scissors>', '[OPEN] <envelope>', '[FIND] <creditcard>', '[GRAB] <creditcard>']
}
|
Scene_Objects:['sheets', 'toilet', 'walllamp', 'bathroom', 'detergent', 'knifeblock', 'bathroom_counter', 'purse', 'alcohol', 'bookmark', 'stovefan', 'toaster', 'stereo', 'food_jam', 'dining_room', 'powersocket', 'food_food', 'mouthwash', 'tray', 'after_shave', 'doorjamb', 'shaving_cream', 'mouse', 'kitchen_counter', 'cupboard', 'controller', 'hairdryer', 'sink', 'home_office', 'laser_pointer']
Task:Walk through
response:
| {
"thoughts": "Walk through the hallway.",
"actions": [
"[WALK] <home_office>",
"[WALK] <dining_room>",
"[WALK] <home_office>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['dry_pasta', 'pot', 'filing_cabinet', 'tablelamp', 'microwave', 'walllamp', 'trashcan', 'floor', 'tea_bag', 'thread', 'toaster', 'ceilinglamp', 'plate', 'dish_soap', 'wall', 'bed', 'coffe_maker', 'food_food', 'check', 'oven_mitts', 'tray', 'doorjamb', 'pencil', 'kitchen_counter', 'hairbrush', 'cupboard', 'hair', 'controller', 'bathroom_cabinet', 'dishwasher']
Task:Wash dishes with dishwasher
response:
{
"thoughts": Walk to the kitchen. Open the dishwasher. Grab plate and put it in the dishwasher. Grab dish soap and put it in the dishwasher. Switch on the dishwasher.,
"actions": ['[WALK] <dining_room>', '[WALK] <dishwasher>', '[FIND] <dishwasher>', '[OPEN] <dishwasher>', '[FIND] <plate>', '[GRAB] <plate>', '[PUTBACK] <plate> <dishwasher>', '[FIND] <dish_soap>', '[GRAB] <dish_soap>', '[PUTBACK] <dish_soap> <dishwasher>', '[CLOSE] <dishwasher>', '[SWITCHON] <dishwasher>']
}
|
Scene_Objects:['spectacles', 'tablelamp', 'toilet', 'walllamp', 'orchid', 'hanger', 'floor', 'ceiling', 'shampoo', 'bedroom', 'desk', 'envelope', 'table_cloth', 'bookmark', 'brush', 'toaster', 'window', 'couch', 'dustpan', 'food_jam', 'pillow', 'dining_room', 'wall', 'photoframe', 'check', 'tray', 'curtain', 'lighter', 'dresser', 'light']
Task:Gaze out window
response:
| {
"thoughts": "Look at the yard from the window",
"actions": [
"[WALK] <home_office>",
"[WALK] <window>",
"[FIND] <window>",
"[TURNTO] <window>",
"[LOOKAT] <window>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['glue', 'toilet', 'freezer', 'wallshelf', 'hanger', 'bathroom_counter', 'bookshelf', 'mail', 'brush', 'mat', 'shoe-shine_kit', 'homework', 'closetdrawer', 'couch', 'food_orange', 'towel', 'dining_room', 'wall', 'powersocket', 'box', 'novel', 'check', 'coffe_maker', 'tray', 'doorjamb', 'diary', 'cupboard', 'home_office', 'bathroom_cabinet', 'soap']
Task:Read book
response:
{
"thoughts": Pick up the book, open to current page, read the words.,
"actions": ['[WALK] <home_office>', '[WALK] <novel>', '[FIND] <novel>', '[GRAB] <novel>', '[READ] <novel>']
}
|
Scene_Objects:['glue', 'chair', 'bathroom', 'detergent', 'drawing', 'bathroom_counter', 'floor', 'ceiling', 'keyboard', 'purse', 'face', 'mat', 'tvstand', 'faucet', 'mousepad', 'wall', 'bench', 'face_soap', 'newspaper', 'novel', 'ice', 'curtain', 'doorjamb', 'chessboard', 'dresser', 'conditioner', 'sink', 'bathroom_cabinet', 'light', 'table']
Task:Wash face
response:
| {
"thoughts": "Run warm water. Cleanse my face with soap. Rinse my face with water.",
"actions": [
"[WALK] <bathroom>",
"[WALK] <sink>",
"[FIND] <faucet>",
"[SWITCHON] <faucet>",
"[FIND] <face_soap>",
"[GRAB] <face_soap>",
"[FIND] <face>",
"[SCRUB] <face>",
"[PUTOBJBACK] <face_soap>",
"[WASH] <face>",
"[RINSE] <face>",
"[SWITCHOFF] <faucet>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'tablelamp', 'walllamp', 'woman', 'drawing', 'phone', 'desk', 'man', 'toaster', 'laptop', 'mat', 'shower', 'electric_shaver', 'oil', 'form', 'pillow', 'dining_room', 'oven', 'shelf', 'bed', 'standingmirror', 'toothbrush_holder', 'tray', 'curtain', 'doorjamb', 'mouse', 'door', 'bathroom_cabinet', 'tooth_paste', 'scrabble']
Task:Greet guests
response:
{
"thoughts": Answer the door. Smile and give a warm hello, or other appropriate greeting. With newcomers to your home, offer your hand to be shook. With old friends it is appropriate to hug, or kiss one another on the cheek.,
"actions": ['[WALK] <home_office>', '[WALK] <man>', '[FIND] <man>', '[GREET] <man>', '[FIND] <woman>', '[GREET] <woman>']
}
|
Scene_Objects:['spectacles', 'pot', 'filing_cabinet', 'measuring_cup', 'walllamp', 'detergent', 'cat', 'milk', 'knifeblock', 'floor', 'ceiling', 'character', 'folder', 'bookshelf', 'piano_bench', 'table_cloth', 'faucet', 'window', 'mousepad', 'dining_room', 'wall', 'powersocket', 'food_cheese', 'bed', 'check', 'kitchen_counter', 'cupboard', 'sink', 'clothes_scarf', 'clothes_skirt']
Task:Wipe down sink
response:
| {
"thoughts": "Use a cloth to wipe the edge of the sink. Then wipe the bowl of the sink as well.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <rag>",
"[FIND] <rag>",
"[GRAB] <rag>",
"[WALK] <sink>",
"[WIPE] <sink>",
"[PUTOBJBACK] <rag>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'pot', 'food_pizza', 'tablelamp', 'mop', 'chair', 'freezer', 'walllamp', 'dough', 'drawing', 'knifeblock', 'wallshelf', 'orchid', 'floor', 'ceiling', 'mop_bucket', 'toaster', 'stovefan', 'faucet', 'bowl', 'wall', 'oven', 'bench', 'toy', 'tray', 'kitchen_counter', 'dresser', 'cupboard', 'door', 'sink']
Task:Cook some food
response:
{
"thoughts": go to the kitchen and cook some thing to eat,
"actions": ['[WALK] <dining_room>', '[WALK] <freezer>', '[FIND] <freezer>', '[OPEN] <freezer>', '[FIND] <oven>', '[OPEN] <oven>', '[FIND] <food_pizza>', '[GRAB] <food_pizza>', '[PUTIN] <food_pizza> <oven>', '[SWITCHON] <oven>']
}
|
Scene_Objects:['pot', 'filing_cabinet', 'scissors', 'chair', 'freezer', 'walllamp', 'orchid', 'cpuscreen', 'bathroom_counter', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'stovefan', 'mat', 'ceilinglamp', 'shower', 'faucet', 'mousepad', 'food_orange', 'wall', 'powersocket', 'wooden_spoon', 'after_shave', 'doorjamb', 'shaving_cream', 'mouse', 'door', 'table']
Task:Computer work
response:
| {
"thoughts": "Find the computer, Turn on the computer, find keyboard, find mouse, go online",
"actions": [
"[WALK] <home_office>",
"[WALK] <chair>",
"[FIND] <chair>",
"[SIT] <chair>",
"[FIND] <computer>",
"[SWITCHON] <computer>",
"[FIND] <mouse>",
"[GRAB] <mouse>",
"[TURNTO] <computer>",
"[POINTAT] <computer>",
"[TURNTO] <computer>",
"[LOOKAT] <computer>",
"[PUTOBJBACK] <mouse>",
"[FIND] <keyboard>",
"[TYPE] <keyboard>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['glue', 'mop', 'toilet', 'cat', 'trashcan', 'ceilingfan', 'drawing', 'knifeblock', 'orchid', 'floor', 'ceiling', 'computer', 'clothes_jacket', 'table_cloth', 'stovefan', 'ceilinglamp', 'tvstand', 'faucet', 'window', 'couch', 'wall', 'nightstand', 'food_food', 'mouthwash', 'television', 'food_donut', 'curtain', 'after_shave', 'dresser', 'table']
Task:Look at painting
response:
{
"thoughts": Walk to the painting. Look up at the painting. Admire it on the wall.,
"actions": ['[WALK] <home_office>', '[WALK] <drawing>', '[FIND] <drawing>', '[TURNTO] <drawing>', '[LOOKAT] <drawing>']
}
|
Scene_Objects:['walllamp', 'drawing', 'orchid', 'hanger', 'floor', 'ceiling', 'desk', 'remote_control', 'ceilinglamp', 'tvstand', 'mat', 'window', 'couch', 'clothes_pants', 'form', 'pillow', 'towel', 'wall', 'powersocket', 'bench', 'newspaper', 'television', 'curtain', 'doorjamb', 'mouse', 'hair', 'door', 'bathroom_cabinet', 'table', 'dishwasher']
Task:Watch TV
response:
| {
"thoughts": "SIT ON THE COUCH, TURN TV ON WITH REMOTE, FIND A SHOW",
"actions": [
"[WALK] <home_office>",
"[WALK] <couch>",
"[FIND] <couch>",
"[SIT] <couch>",
"[FIND] <remote_control>",
"[GRAB] <remote_control>",
"[FIND] <television>",
"[SWITCHON] <television>",
"[PUTOBJBACK] <remote_control>",
"[TURNTO] <television>",
"[WATCH] <television>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'tablelamp', 'walllamp', 'cat', 'milk', 'orchid', 'drawing', 'bills', 'hanger', 'floor', 'ceiling', 'phone', 'character', 'bookshelf', 'toaster', 'ceilinglamp', 'mat', 'stereo', 'picture', 'closetdrawer', 'pillow', 'wall', 'nightstand', 'powersocket', 'basket_for_clothes', 'photoframe', 'doorjamb', 'door', 'light', 'table']
Task:Look at painting
response:
{
"thoughts": Walk to the painting. Look up at the painting. Admire it on the wall.,
"actions": ['[WALK] <home_office>', '[WALK] <drawing>', '[FIND] <drawing>', '[TURNTO] <drawing>', '[LOOKAT] <drawing>']
}
|
Scene_Objects:['pot', 'filing_cabinet', 'tablelamp', 'chair', 'freezer', 'bathroom', 'food_butter', 'drawing', 'food_egg', 'floor', 'computer', 'mat', 'tvstand', 'stereo', 'laptop', 'clothes_pants', 'towel', 'wall', 'nightstand', 'tape', 'bed', 'food_food', 'coffe_maker', 'television', 'oven_mitts', 'tray', 'curtain', 'diary', 'cards', 'dishwasher']
Task:Listen to music
response:
| {
"thoughts": "Turn on radio, put on favorite channel, listen to music.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <stereo>",
"[FIND] <stereo>",
"[SWITCHON] <stereo>",
"[FIND] <bed>",
"[LIE] <bed>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'tablelamp', 'juice', 'microwave', 'chair', 'trashcan', 'drawing', 'cpuscreen', 'wallshelf', 'floor', 'ceiling', 'computer', 'table_cloth', 'tvstand', 'shower', 'mousepad', 'dining_room', 'wall', 'nightstand', 'powersocket', 'photoframe', 'food_food', 'television', 'tray', 'doorjamb', 'cupboard', 'sink', 'bathroom_cabinet', 'light', 'board_game']
Task:Turn on light
response:
{
"thoughts": walk into living room, walk to light, turn on light switch.,
"actions": ['[WALK] <home_office>', '[WALK] <light>', '[SWITCHON] <light>']
}
|
Scene_Objects:['food_bread', 'drawing', 'bathroom_counter', 'floor', 'ceiling', 'face', 'toaster', 'mat', 'faucet', 'foundation', 'mousepad', 'towel', 'dining_room', 'broom', 'wall', 'bowl', 'bench', 'face_soap', 'food_cheese', 'coin', 'water', 'after_shave', 'rag', 'curtain', 'mouse', 'conditioner', 'sink', 'napkin', 'bathroom_cabinet', 'hands_both']
Task:Wash face
response:
| {
"thoughts": "Turn on water faucet. Get rag wet. Get face soap out. Squirt face soap in hands and put it on face. Rub soap into face. Wash soap off of face. Dry face off on the hand towel. Hang out rag and hand towel.",
"actions": [
"[WALK] <bathroom>",
"[WALK] <rag>",
"[FIND] <rag>",
"[GRAB] <rag>",
"[WALK] <sink>",
"[FIND] <faucet>",
"[SWITCHON] <faucet>",
"[PUTBACK] <rag> <sink>",
"[GRAB] <rag>",
"[FIND] <face_soap>",
"[GRAB] <face_soap>",
"[POUR] <face_soap> <rag>",
"[PUTOBJBACK] <face_soap>",
"[FIND] <face>",
"[SCRUB] <face>",
"[PUTBACK] <rag> <sink>",
"[FIND] <water>",
"[GRAB] <water>",
"[FIND] <hands_both>",
"[POUR] <water> <hands_both>",
"[RINSE] <face>",
"[WASH] <rag>",
"[GRAB] <rag>",
"[PUTOBJBACK] <rag>",
"[SWITCHOFF] <faucet>",
"[FIND] <towel>",
"[GRAB] <towel>",
"[WIPE] <face>",
"[PUTOBJBACK] <towel>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'pot', 'filing_cabinet', 'tablelamp', 'freezer', 'bathroom', 'milk', 'drawing', 'floor', 'ceiling', 'bedroom', 'alcohol', 'computer', 'table_cloth', 'stovefan', 'mat', 'shower', 'oil', 'couch', 'pillow', 'wall', 'cutting_board', 'newspaper', 'food_food', 'television', 'kettle', 'kitchen_counter', 'cupboard', 'clothes_dress', 'shoe_rack']
Task:Put groceries in Fridge
response:
{
"thoughts": Walk to kitchen. Find groceries. Grab groceries. Find fridge. Walk to fridge. Put groceries in fridge.,
"actions": ['[WALK] <dining_room>', '[WALK] <food_food>', '[FIND] <food_food>', '[GRAB] <food_food>', '[FIND] <freezer>', '[WALK] <freezer>', '[OPEN] <freezer>', '[PUTIN] <food_food> <freezer>']
}
|
Scene_Objects:['food_bread', 'food_ice_cream', 'freezer', 'milk', 'drawing', 'knife', 'cpuscreen', 'kitchen_cabinet', 'floor', 'ceiling', 'dvd_player', 'stamp', 'desk', 'keyboard', 'computer', 'button', 'mat', 'plate', 'ceilinglamp', 'mousepad', 'candle', 'pillow', 'wall', 'bench', 'powersocket', 'cup', 'food_food', 'doorjamb', 'mouse', 'door', 'napkin', 'table', 'light']
Task:Cut bread
response:
| {
"thoughts": "I get a slice of bread, grab a knife, and then cut the piece of bread in half.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <kitchen_cabinet>",
"[FIND] <kitchen_cabinet>",
"[OPEN] <kitchen_cabinet>",
"[FIND] <knife>",
"[GRAB] <knife>",
"[FIND] <plate>",
"[GRAB] <plate>",
"[CLOSE] <kitchen_cabinet>",
"[FIND] <table>",
"[PUTBACK] <plate> <table>",
"[PUTBACK] <knife> <table>",
"[FIND] <freezer>",
"[OPEN] <freezer>",
"[FIND] <food_bread>",
"[GRAB] <food_bread>",
"[CLOSE] <freezer>",
"[PUTBACK] <food_bread> <plate>",
"[GRAB] <knife>",
"[CUT] <food_bread>",
"[PUTOBJBACK] <knife>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'tablelamp', 'food_ice_cream', 'walllamp', 'trashcan', 'ceilingfan', 'drawing', 'longboard', 'floor', 'bookshelf', 'computer', 'faucet', 'balanceball', 'window', 'iron', 'food_peanut_butter', 'food_jam', 'wall', 'nightstand', 'bench', 'powersocket', 'basket_for_clothes', 'novel', 'check', 'coffee_filter', 'shaving_cream', 'pencil', 'maindoor', 'sink', 'hairdryer']
Task:Pick up phone
response:
{
"thoughts": Enter the Home office, then walk to the phone, pickup the phone.,
"actions": ['[WALK] <home_office>', '[WALK] <phone>', '[GRAB] <phone>']
}
|
Scene_Objects:['pot', 'juice', 'jelly', 'freezer', 'walllamp', 'nail_polish', 'knifeblock', 'drawing', 'cpuscreen', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'button', 'stovefan', 'ceilinglamp', 'mat', 'faucet', 'mousepad', 'pillow', 'wall', 'oven', 'powersocket', 'bench', 'cup', 'food_food', 'food_rice', 'tray', 'doorjamb', 'mouse', 'kitchen_counter', 'cupboard', 'door', 'sink', 'light', 'table', 'board_game']
Task:Grab some juice
response:
| {
"thoughts": "I go to the fridge, and grab some juice out of it. I then get a glass, and pour the juice into the glass.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <cupboard>",
"[FIND] <cupboard>",
"[OPEN] <cupboard>",
"[FIND] <cup>",
"[GRAB] <cup>",
"[CLOSE] <cupboard>",
"[WALK] <freezer>",
"[OPEN] <freezer>",
"[FIND] <juice>",
"[GRAB] <juice>",
"[POUR] <juice> <cup>",
"[PUTOBJBACK] <juice>",
"[CLOSE] <freezer>",
"[FIND] <table>",
"[PUTBACK] <cup> <table>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'food_ice_cream', 'toilet', 'walllamp', 'dough', 'drawing', 'knifeblock', 'cpuscreen', 'clothes_underwear', 'floor', 'ceiling', 'character', 'bedroom', 'window', 'couch', 'pillow', 'wall', 'powersocket', 'basket_for_clothes', 'bed', 'food_food', 'television', 'doorjamb', 'mouse', 'pencil', 'dishrack', 'door', 'home_office', 'light', 'bathroom_cabinet']
Task:Turn off light
response:
{
"thoughts": Grasp light switch, flip light switch.,
"actions": ['[WALK] <bedroom>', '[WALK] <light>', '[FIND] <light>', '[TURNTO] <light>', '[SWITCHOFF] <light>']
}
|
Scene_Objects:['pot', 'crayon', 'tea', 'beer', 'microwave', 'toilet', 'trashcan', 'food_carrot', 'knifeblock', 'cpuscreen', 'bathroom_counter', 'floor', 'character', 'bedroom', 'desk', 'keyboard', 'bookshelf', 'computer', 'ceilinglamp', 'window', 'dining_room', 'food_kiwi', 'nightstand', 'bed', 'photoframe', 'doorjamb', 'dishrack', 'cupboard', 'sink', 'home_office']
Task:Open bathroom window
response:
| {
"thoughts": "Make sure bathroom window is unlocked. Lift up bathroom window so it is open.",
"actions": [
"[WALK] <bathroom>",
"[WALK] <window>",
"[FIND] <window>",
"[OPEN] <window>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['tablelamp', 'chair', 'walllamp', 'nail_polish', 'trashcan', 'orchid', 'drawing', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'ceilinglamp', 'tvstand', 'mousepad', 'closetdrawer', 'wall', 'powersocket', 'bench', 'bed', 'coffe_maker', 'television', 'food_donut', 'doorjamb', 'mouse', 'door', 'table', 'shoe_rack']
Task:Work
response:
{
"thoughts": Walk to living-room. Look at the desk where Computer stays. Sit in chair. Switch on computer. Work on computer. Switch off computer.,
"actions": ['[WALK] <home_office>', '[WALK] <desk>', '[FIND] <desk>', '[TURNTO] <desk>', '[LOOKAT] <desk>', '[FIND] <chair>', '[SIT] <chair>', '[FIND] <computer>', '[SWITCHON] <computer>', '[TURNTO] <computer>', '[WATCH] <computer>', '[SWITCHOFF] <computer>']
}
|
Scene_Objects:['pot', 'food_ice_cream', 'freezer', 'walllamp', 'milk', 'knifeblock', 'cpuscreen', 'floor', 'ceiling', 'desk', 'keyboard', 'alcohol', 'computer', 'stovefan', 'ceilinglamp', 'faucet', 'mousepad', 'wall', 'oven', 'powersocket', 'cup', 'ice', 'tray', 'doorjamb', 'mouse', 'kitchen_counter', 'cupboard', 'door', 'sink', 'light']
Task:Get something to drink
response:
| {
"thoughts": "Walk into the kitchen and to the cupboard to get a cup, walk to the fridge to look for a beverage to enjoy, open the freezer and get ice, pour beverage and enjoy",
"actions": [
"[WALK] <dining_room>",
"[WALK] <cupboard>",
"[FIND] <cupboard>",
"[OPEN] <cupboard>",
"[FIND] <cup>",
"[GRAB] <cup>",
"[CLOSE] <cupboard>",
"[WALK] <freezer>",
"[OPEN] <freezer>",
"[FIND] <milk>",
"[GRAB] <milk>",
"[CLOSE] <freezer>",
"[POUR] <milk> <cup>",
"[DRINK] <cup>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['blender', 'freezer', 'walllamp', 'bathroom', 'drawing', 'clothes_underwear', 'hanger', 'floor', 'ceiling', 'character', 'keyboard', 'brush', 'tvstand', 'stereo', 'window', 'closetdrawer', 'towel', 'wall', 'powersocket', 'tape', 'food_food', 'television', 'curtain', 'doorjamb', 'vacuum_cleaner', 'dresser', 'door', 'clothes_scarf', 'dishwasher', 'board_game']
Task:vacuum carpet
response:
{
"thoughts": I bring my vacuum cleaner into the living room. I plug it into the wall. I press the on switch on the vacuum cleaner. I push the vacuum cleaner back and forth over the length and width of the carpet until I have vacuumed the entire carpet. I turn the vacuum cleaner off. I take the vacuum cleaner back to the hall closet.,
"actions": ['[WALK] <home_office>', '[WALK] <dresser>', '[OPEN] <dresser>', '[FIND] <vacuum_cleaner>', '[GRAB] <vacuum_cleaner>', '[PULL] <vacuum_cleaner>', '[PLUGIN] <vacuum_cleaner>', '[SWITCHON] <vacuum_cleaner>', '[PULL] <vacuum_cleaner>', '[PUSH] <vacuum_cleaner>', '[PULL] <vacuum_cleaner>', '[PUSH] <vacuum_cleaner>', '[PULL] <vacuum_cleaner>', '[PUSH] <vacuum_cleaner>', '[SWITCHOFF] <vacuum_cleaner>', '[PLUGOUT] <vacuum_cleaner>', '[WALK] <dresser>', '[PUTIN] <vacuum_cleaner> <dresser>', '[CLOSE] <dresser>']
}
|
Scene_Objects:['tablelamp', 'chair', 'freezer', 'cat', 'drawing', 'knifeblock', 'cpuscreen', 'floor', 'folder', 'desk', 'keyboard', 'computer', 'faucet', 'stereo', 'mousepad', 'food_peanut_butter', 'wall', 'nightstand', 'powersocket', 'bed', 'novel', 'check', 'toothbrush_holder', 'curtain', 'doorjamb', 'mouse', 'kitchen_counter', 'door', 'napkin', 'light']
Task:Read
response:
| {
"thoughts": "I like to read books in my bedroom.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <desk>",
"[FIND] <novel>",
"[GRAB] <novel>",
"[WALK] <bed>",
"[LIE] <bed>",
"[READ] <novel>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'pot', 'filing_cabinet', 'tea', 'chair', 'freezer', 'ground_coffee', 'drawing', 'orchid', 'floor', 'purse', 'faucet', 'balanceball', 'food_noodles', 'food_peanut_butter', 'wall', 'powersocket', 'toy', 'bed', 'food_food', 'check', 'food_donut', 'doorjamb', 'pencil', 'laundry_detergent', 'door', 'bag', 'napkin', 'light', 'table']
Task:Pick up toys
response:
{
"thoughts": Grab toys off floor. Put it in a container.,
"actions": ['[WALK] <bedroom>', '[WALK] <toy>', '[FIND] <toy>', '[GRAB] <toy>', '[WALK] <filing_cabinet>', '[OPEN] <filing_cabinet>', '[PUTBACK] <toy> <filing_cabinet>', '[FIND] <toy>', '[GRAB] <toy>', '[WALK] <filing_cabinet>', '[PUTBACK] <toy> <filing_cabinet>', '[FIND] <toy>', '[GRAB] <toy>', '[WALK] <filing_cabinet>', '[PUTBACK] <toy> <filing_cabinet>', '[CLOSE] <filing_cabinet>']
}
|
Scene_Objects:['pot', 'tablelamp', 'microwave', 'freezer', 'walllamp', 'food_carrot', 'drawing', 'clothes_underwear', 'bathroom_counter', 'floor', 'bookshelf', 'keyboard', 'computer', 'stovefan', 'ceilinglamp', 'tvstand', 'floor_lamp', 'foundation', 'couch', 'pillow', 'bowl', 'dining_room', 'wall', 'nightstand', 'oven', 'bed', 'food_donut', 'console', 'cupboard', 'bathroom_cabinet']
Task:Turn on lights
response:
| {
"thoughts": "Walk to your lamp, switch it on, and lay on your bed",
"actions": [
"[WALK] <bedroom>",
"[WALK] <floor_lamp>",
"[FIND] <floor_lamp>",
"[TURNTO] <floor_lamp>",
"[SWITCHON] <floor_lamp>",
"[FIND] <bed>",
"[LIE] <bed>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'scissors', 'jelly', 'walllamp', 'bathroom', 'ceilingfan', 'drawing', 'hanger', 'floor', 'ceiling', 'desk', 'remote_control', 'computer', 'ceilinglamp', 'tvstand', 'balanceball', 'shoe-shine_kit', 'window', 'couch', 'food_jam', 'wall', 'novel', 'television', 'curtain', 'doorjamb', 'comb', 'clothes_dress', 'sink', 'home_office', 'table']
Task:Change TV channel
response:
{
"thoughts": first i will go to living room and then take the remote and swtitch on television after that il change the channel,
"actions": ['[WALK] <home_office>', '[WALK] <television>', '[FIND] <television>', '[SWITCHON] <television>', '[FIND] <remote_control>', '[TURNTO] <remote_control>', '[POINTAT] <remote_control>', '[TOUCH] <remote_control>', '[TURNTO] <television>', '[WATCH] <television>']
}
|
Scene_Objects:['glue', 'food_bread', 'filing_cabinet', 'bathroom', 'ceiling', 'phone', 'keyboard', 'purse', 'bookshelf', 'laptop', 'ceilinglamp', 'faucet', 'nightstand', 'bench', 'photoframe', 'bed', 'clothes_gloves', 'food_food', 'coffe_maker', 'television', 'toothbrush_holder', 'curtain', 'shaving_cream', 'pencil', 'dresser', 'conditioner', 'door', 'spoon', 'bathroom_cabinet', 'table']
Task:Shut front door
response:
| {
"thoughts": "Close the storm door. Lock the storm door.",
"actions": [
"[WALK] <home_office>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['microwave', 'drawing', 'orchid', 'cpuscreen', 'floor', 'ceiling', 'mat', 'window', 'clothes_socks', 'couch', 'pillow', 'towel', 'broom', 'wall', 'bench', 'oven', 'toy', 'bed', 'coffe_maker', 'television', 'wooden_spoon', 'curtain', 'rag', 'doorjamb', 'food_onion', 'towel_rack', 'mouse', 'bathroom_cabinet', 'table', 'scrabble']
Task:Relax on sofa
response:
{
"thoughts": Walk to living room. Find couch. Sit on couch,
"actions": ['[WALK] <home_office>', '[WALK] <couch>', '[FIND] <couch>', '[SIT] <couch>']
}
|
Scene_Objects:['tablelamp', 'juice', 'food_ice_cream', 'chair', 'walllamp', 'detergent', 'drawing', 'cpuscreen', 'bathroom_counter', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'mat', 'tvstand', 'mousepad', 'clothes_hat', 'towel', 'wall', 'powersocket', 'bench', 'photoframe', 'television', 'curtain', 'doorjamb', 'mouse', 'shoes', 'door', 'bathroom_cabinet']
Task:Put in chair
response:
| {
"thoughts": "Take a comfortable chair. Place it in the entrance hall",
"actions": [
"[WALK] <home_office>",
"[WALK] <chair>",
"[FIND] <chair>",
"[GRAB] <chair>",
"[WALK] <home_office>",
"[WALK] <floor>",
"[FIND] <floor>",
"[PUTBACK] <chair> <floor>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'microwave', 'chair', 'freezer', 'walllamp', 'floor', 'character', 'bookshelf', 'computer', 'toaster', 'mat', 'plate', 'window', 'food_noodles', 'food_orange', 'wall', 'oven', 'photoframe', 'keys', 'bed', 'coffe_maker', 'toothbrush_holder', 'doorjamb', 'kitchen_counter', 'comb', 'cupboard', 'clothes_dress', 'napkin', 'home_office', 'dishwasher']
Task:Wash dishes with dishwasher
response:
{
"thoughts": In the kitchen, open up the dishwasher. Take plates from the sink and put them in the dishwasher one by one. Close the dishwasher. Program it. Push start.,
"actions": ['[WALK] <dining_room>', '[WALK] <dishwasher>', '[FIND] <dishwasher>', '[OPEN] <dishwasher>', '[FIND] <plate>', '[GRAB] <plate>', '[PUTBACK] <plate> <dishwasher>', '[FIND] <plate>', '[GRAB] <plate>', '[PUTBACK] <plate> <dishwasher>', '[FIND] <plate>', '[GRAB] <plate>', '[PUTBACK] <plate> <dishwasher>', '[CLOSE] <dishwasher>', '[SWITCHON] <dishwasher>']
}
|
Scene_Objects:['sponge', 'band-aids', 'toothbrush', 'orchid', 'phone', 'desk', 'keyboard', 'bookshelf', 'computer', 'toaster', 'faucet', 'picture', 'shower', 'mousepad', 'candle', 'food_orange', 'oven', 'basket_for_clothes', 'bed', 'check', 'food_food', 'television', 'tray', 'after_shave', 'headset', 'comb', 'dresser', 'laundry_detergent', 'napkin', 'bathroom_cabinet']
Task:Sit in chair
response:
| {
"thoughts": "I sit in a chair to rest and eat.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <chair>",
"[FIND] <chair>",
"[PULL] <chair>",
"[SIT] <chair>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['glue', 'filing_cabinet', 'microwave', 'freezer', 'detergent', 'drawing', 'floor', 'ceiling', 'table_cloth', 'stovefan', 'ceilinglamp', 'iron', 'faucet', 'window', 'homework', 'bowl', 'wall', 'wall_clock', 'bench', 'shelf', 'newspaper', 'mouthwash', 'food_donut', 'doorjamb', 'coffee_pot', 'door', 'sink', 'bathroom_cabinet', 'light', 'board_game']
Task:Turn light off
response:
{
"thoughts": Put the light switch into the down, or off, position.,
"actions": ['[WALK] <bedroom>', '[WALK] <light>', '[SWITCHOFF] <light>']
}
|
Scene_Objects:['pot', 'filing_cabinet', 'freezer', 'blow_dryer', 'walllamp', 'drawing', 'knifeblock', 'cpuscreen', 'bathroom_counter', 'ceiling', 'character', 'faucet', 'picture', 'iron', 'mousepad', 'bowl', 'wall', 'powersocket', 'bench', 'photoframe', 'toilet_paper', 'coffe_maker', 'toothbrush_holder', 'tray', 'doorjamb', 'dishrack', 'sink', 'bathroom_cabinet', 'home_office', 'light']
Task:Get toilet paper
response:
| {
"thoughts": "There are extra toilet papers in the bottom cabinet.",
"actions": [
"[WALK] <bathroom>",
"[WALK] <bathroom_cabinet>",
"[FIND] <bathroom_cabinet>",
"[OPEN] <bathroom_cabinet>",
"[FIND] <toilet_paper>",
"[GRAB] <toilet_paper>",
"[CLOSE] <bathroom_cabinet>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['crayon', 'trashcan', 'orchid', 'cpuscreen', 'ceiling', 'bedroom', 'table_cloth', 'ceilinglamp', 'tvstand', 'mousepad', 'closetdrawer', 'dining_room', 'wall', 'nightstand', 'powersocket', 'bench', 'bed', 'novel', 'food_food', 'mouthwash', 'coffe_maker', 'oven_mitts', 'curtain', 'doorjamb', 'cards', 'dresser', 'cupboard', 'bathtub', 'home_office', 'light']
Task:Read book
response:
{
"thoughts": Go to the book shelf, get a book, open the book and read the book.,
"actions": ['[WALK] <home_office>', '[WALK] <novel>', '[FIND] <novel>', '[GRAB] <novel>', '[READ] <novel>']
}
|
Scene_Objects:['spectacles', 'pot', 'sheets', 'walllamp', 'knifeblock', 'drawing', 'orchid', 'floor', 'bedroom', 'mail', 'food_bacon', 'laptop', 'mat', 'plate', 'faucet', 'food_orange', 'pillow', 'wall', 'bench', 'box', 'bed', 'photoframe', 'mouse', 'kitchen_counter', 'cupboard', 'sink', 'napkin', 'bathroom_cabinet', 'table', 'tooth_paste']
Task:Bring dirty plate to sink
response:
| {
"thoughts": "Stand up from the table. Pick up dirty plate. Walk to sink. Put plate in sink.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <table>",
"[FIND] <table>",
"[TURNTO] <table>",
"[FIND] <plate>",
"[GRAB] <plate>",
"[WALK] <dining_room>",
"[WALK] <sink>",
"[FIND] <sink>",
"[PUTBACK] <plate> <sink>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'microwave', 'freezer', 'ground_coffee', 'cpuscreen', 'floor', 'ceiling', 'keyboard', 'toaster', 'ceilinglamp', 'mat', 'faucet', 'food_orange', 'bowl', 'wall', 'wall_clock', 'cutting_board', 'bed', 'photoframe', 'coffe_maker', 'mouthwash', 'coffee_filter', 'water', 'doorjamb', 'pencil', 'kitchen_counter', 'hair', 'controller', 'sink', 'soap']
Task:Make coffee
response:
{
"thoughts": Open coffee maker. Put filter in main basket, put ground coffee in filter, fill reservoir with water, turn on coffee maker.,
"actions": ['[WALK] <dining_room>', '[WALK] <coffe_maker>', '[FIND] <coffe_maker>', '[OPEN] <coffe_maker>', '[FIND] <coffee_filter>', '[GRAB] <coffee_filter>', '[PUTBACK] <coffee_filter> <coffe_maker>', '[FIND] <ground_coffee>', '[GRAB] <ground_coffee>', '[PUTBACK] <ground_coffee> <coffe_maker>', '[GRAB] <ground_coffee>', '[PUTOBJBACK] <ground_coffee>', '[WALK] <water>', '[FIND] <water>', '[GRAB] <water>', '[POUR] <water> <coffe_maker>', '[CLOSE] <coffe_maker>', '[SWITCHON] <coffe_maker>']
}
|
Scene_Objects:['sponge', 'food_pizza', 'filing_cabinet', 'microwave', 'chair', 'walllamp', 'orchid', 'knifeblock', 'bathroom_counter', 'ceiling', 'phone', 'stamp', 'keyboard', 'thread', 'computer', 'stovefan', 'toaster', 'plate', 'shower', 'mousepad', 'form', 'wall', 'food_cheese', 'bed', 'console', 'headset', 'dresser', 'spoon', 'bathroom_cabinet', 'bag']
Task:Walk to room
response:
| {
"thoughts": "Leave the living room and enter the hall",
"actions": [
"[WALK] <home_office>",
"[WALK] <home_office>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'filing_cabinet', 'toilet', 'freezer', 'bathroom', 'detergent', 'bathroom_counter', 'floor', 'bedroom', 'toaster', 'plate', 'shower', 'dining_room', 'nightstand', 'oven', 'cup', 'coffe_maker', 'food_food', 'television', 'tray', 'kitchen_counter', 'dresser', 'door', 'sink', 'bathtub', 'home_office', 'table', 'dishwasher', 'soap', 'board_game']
Task:Wash dishes with dishwasher
response:
{
"thoughts": Walk to Kitchen, find dishwasher. Find vessels to be washed. Open dishwasher, put vessels in dish washer, close dish washer and switch it on.,
"actions": ['[WALK] <dining_room>', '[WALK] <dishwasher>', '[FIND] <dishwasher>', '[OPEN] <dishwasher>', '[FIND] <cup>', '[GRAB] <cup>', '[PUTBACK] <cup> <dishwasher>', '[FIND] <plate>', '[GRAB] <plate>', '[GRAB] <cup>', '[PUTBACK] <cup> <plate>', '[GRAB] <cup>', '[PUTBACK] <cup> <dishwasher>', '[CLOSE] <dishwasher>', '[SWITCHON] <dishwasher>']
}
|
Scene_Objects:['juice', 'beer', 'freezer', 'walllamp', 'drawing', 'orchid', 'cpuscreen', 'floor', 'ceiling', 'character', 'desk', 'folder', 'keyboard', 'computer', 'ceilinglamp', 'window', 'mousepad', 'couch', 'pillow', 'bowl', 'food_kiwi', 'wall', 'powersocket', 'food_food', 'curtain', 'doorjamb', 'mouse', 'door', 'light', 'table']
Task:Drink
response:
| {
"thoughts": "Get a can of beer, open it, sit on couch, relax",
"actions": [
"[WALK] <dining_room>",
"[WALK] <freezer>",
"[FIND] <freezer>",
"[OPEN] <freezer>",
"[FIND] <beer>",
"[GRAB] <beer>",
"[CLOSE] <freezer>",
"[WALK] <home_office>",
"[WALK] <couch>",
"[FIND] <couch>",
"[SIT] <couch>",
"[DRINK] <beer>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['fork', 'pot', 'toilet', 'chair', 'bathroom', 'drawing', 'knife', 'clothes_underwear', 'floor', 'mail', 'food_bacon', 'piano_bench', 'stovefan', 'ceilinglamp', 'plate', 'deck_of_cards', 'toaster', 'oil', 'wall', 'wall_clock', 'oven', 'cup', 'novel', 'food_food', 'television', 'oven_mitts', 'cards', 'cupboard', 'conditioner', 'table']
Task:Eat dinner
response:
{
"thoughts": Sit down at the dinning table with my family and eat dinner.,
"actions": ['[WALK] <dining_room>', '[WALK] <table>', '[FIND] <chair>', '[PULL] <chair>', '[SIT] <chair>', '[FIND] <food_food>', '[TURNTO] <food_food>', '[LOOKAT] <food_food>', '[GRAB] <food_food>', '[FIND] <plate>', '[PUTBACK] <food_food> <plate>', '[GRAB] <food_food>', '[PUTOBJBACK] <food_food>', '[FIND] <fork>', '[GRAB] <fork>', '[EAT] <plate>']
}
|
Scene_Objects:['chair', 'ground_coffee', 'bathroom', 'detergent', 'dough', 'knifeblock', 'drawing', 'food_egg', 'floor', 'bedroom', 'keyboard', 'purse', 'mop_bucket', 'stovefan', 'mousepad', 'food_orange', 'bed', 'check', 'toilet_paper', 'food_rice', 'tray', 'shaving_cream', 'mouse', 'cd', 'dresser', 'cupboard', 'door', 'bathroom_cabinet', 'clothes_skirt', 'creditcard']
Task:Turn on light
response:
| {
"thoughts": "Twist the lamp switch until the light goes on.",
"actions": [
"[WALK] <home_office>",
"[WALK] <floor_lamp>",
"[FIND] <floor_lamp>",
"[SWITCHON] <floor_lamp>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'toilet', 'detergent', 'hanger', 'floor', 'phone', 'stamp', 'toaster', 'balanceball', 'oil', 'pillow', 'dining_room', 'wall_clock', 'toy', 'newspaper', 'keys', 'photoframe', 'food_food', 'clothes_gloves', 'rag', 'doorjamb', 'mouse', 'dishrack', 'dresser', 'cupboard', 'hairdryer', 'spoon', 'table', 'light', 'scrabble']
Task:Pet cat
response:
{
"thoughts": Pet Cat,
"actions": ['[WALK] <home_office>', '[WALK] <cat>', '[FIND] <cat>', '[WALK] <cat>', '[TURNTO] <cat>', '[LOOKAT] <cat>', '[TOUCH] <cat>']
}
|
Scene_Objects:['dry_pasta', 'pot', 'jelly', 'freezer', 'bathroom', 'trashcan', 'milk', 'toothbrush', 'drawing', 'bathroom_counter', 'floor', 'desk', 'bookshelf', 'alcohol', 'table_cloth', 'faucet', 'shower', 'form', 'powersocket', 'bench', 'bed', 'food_food', 'kitchen_counter', 'headset', 'vacuum_cleaner', 'cupboard', 'door', 'clothes_scarf', 'food_steak', 'soap']
Task:Grab things
response:
| {
"thoughts": "The robot will need some kind of hands or grabbing device to transport objects.",
"actions": [
"[WALK] <novel>",
"[TURNTO] <novel>",
"[GRAB] <novel>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['tablelamp', 'chair', 'orchid', 'drawing', 'cpuscreen', 'bills', 'floor', 'ceiling', 'phone', 'character', 'desk', 'keyboard', 'computer', 'mail', 'mat', 'ceilinglamp', 'tvstand', 'laptop', 'mousepad', 'clothes_socks', 'wall', 'nightstand', 'oven', 'powersocket', 'television', 'mouse', 'shoes', 'comb', 'door', 'light']
Task:Check email
response:
{
"thoughts": Turn on laptop. Connect to Internet. Type in the url. Check for new email messages.,
"actions": ['[WALK] <home_office>', '[WALK] <chair>', '[FIND] <chair>', '[SIT] <chair>', '[FIND] <laptop>', '[SWITCHON] <laptop>', '[FIND] <keyboard>', '[TYPE] <keyboard>', '[TURNTO] <laptop>', '[LOOKAT] <laptop>', '[FIND] <mail>', '[GRAB] <mail>', '[READ] <mail>']
}
|
Scene_Objects:['dry_pasta', 'tablelamp', 'food_salt', 'chair', 'walllamp', 'detergent', 'drawing', 'clothes_underwear', 'floor', 'bedroom', 'toaster', 'ceilinglamp', 'tvstand', 'shower', 'food_noodles', 'garbage_can', 'mousepad', 'microphone', 'wall', 'nightstand', 'food_vegetable', 'bed', 'food_food', 'coffee_filter', 'mouse', 'sink', 'home_office', 'table', 'dishwasher', 'pantry']
Task:Organize pantry
response:
| {
"thoughts": "Remove all perishable foods from the pantry, check dates and throw away any old food. Decide on an efficient ad neat arrangement for the food and replace it in the pantry accordingly.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <pantry>",
"[FIND] <food_food>",
"[GRAB] <food_food>",
"[TURNTO] <food_food>",
"[LOOKAT] <food_food>",
"[FIND] <garbage_can>",
"[PUTBACK] <food_food> <garbage_can>",
"[FIND] <food_vegetable>",
"[GRAB] <food_vegetable>",
"[TURNTO] <food_vegetable>",
"[LOOKAT] <food_vegetable>",
"[PUTBACK] <food_vegetable> <garbage_can>",
"[FIND] <dry_pasta>",
"[GRAB] <dry_pasta>",
"[TURNTO] <dry_pasta>",
"[LOOKAT] <dry_pasta>",
"[PUTOBJBACK] <dry_pasta>",
"[FIND] <food_food>",
"[TURNTO] <food_food>",
"[LOOKAT] <food_food>",
"[PUSH] <food_food>",
"[FIND] <food_noodles>",
"[GRAB] <food_noodles>",
"[TURNTO] <food_noodles>",
"[LOOKAT] <food_noodles>",
"[PUTOBJBACK] <food_noodles>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['glue', 'filing_cabinet', 'scissors', 'microwave', 'ceilingfan', 'drawing', 'knifeblock', 'orchid', 'floor', 'ceiling', 'desk', 'bookshelf', 'purse', 'toaster', 'ceilinglamp', 'tvstand', 'balanceball', 'window', 'couch', 'wall', 'nightstand', 'child', 'cup', 'television', 'curtain', 'centerpiece', 'food_steak', 'hairdryer', 'table', 'vase']
Task:Watch TV
response:
{
"thoughts": Turn on tv. Sit with kids.,
"actions": ['[WALK] <home_office>', '[WALK] <television>', '[SWITCHON] <television>', '[WALK] <couch>', '[FIND] <child>', '[GREET] <child>', '[FIND] <child>', '[GREET] <child>', '[SIT] <couch>', '[TURNTO] <television>', '[WATCH] <television>', '[TURNTO] <television>', '[WATCH] <television>', '[TURNTO] <television>', '[WATCH] <television>']
}
|
Scene_Objects:['tablelamp', 'juice', 'chair', 'freezer', 'walllamp', 'cpuscreen', 'food_egg', 'floor', 'ceiling', 'desk', 'bedroom', 'keyboard', 'computer', 'toaster', 'mat', 'ceilinglamp', 'faucet', 'picture', 'homework', 'mousepad', 'wall', 'oven', 'toy', 'newspaper', 'check', 'television', 'mouse', 'laundry_detergent', 'conditioner', 'laser_pointer']
Task:Push in desk chair
response:
| {
"thoughts": "Push the desk chair until it is under the desk.",
"actions": [
"[WALK] <home_office>",
"[WALK] <desk>",
"[FIND] <chair>",
"[TOUCH] <chair>",
"[PUSH] <chair>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sponge', 'food_salt', 'chair', 'detergent', 'trashcan', 'dough', 'drawing', 'character', 'computer', 'button', 'brush', 'mat', 'couch', 'clothes_pants', 'clothes_hat', 'wall', 'nightstand', 'basket_for_clothes', 'food_cheese', 'rag', 'kitchen_counter', 'shoes', 'vacuum_cleaner', 'laundry_detergent', 'conditioner', 'sink', 'home_office', 'table', 'clothes_shirt', 'washing_machine']
Task:Wash clothes
response:
{
"thoughts": Walk to bathroom, open wash-machine, lift laundry basket, grab cloth and put into wash-machine one by one, put down laundry basket, pour detergent, close wash-machine, turn on wash-machine.,
"actions": ['[WALK] <bathroom>', '[WALK] <washing_machine>', '[FIND] <washing_machine>', '[OPEN] <washing_machine>', '[FIND] <basket_for_clothes>', '[GRAB] <basket_for_clothes>', '[FIND] <clothes_pants>', '[GRAB] <clothes_pants>', '[PUTBACK] <clothes_pants> <washing_machine>', '[FIND] <clothes_shirt>', '[GRAB] <clothes_shirt>', '[PUTBACK] <clothes_shirt> <washing_machine>', '[PUTOBJBACK] <basket_for_clothes>', '[WALK] <laundry_detergent>', '[FIND] <laundry_detergent>', '[GRAB] <laundry_detergent>', '[POUR] <laundry_detergent> <washing_machine>', '[CLOSE] <washing_machine>', '[SWITCHON] <washing_machine>']
}
|
Scene_Objects:['sheets', 'filing_cabinet', 'juice', 'microwave', 'chair', 'walllamp', 'orchid', 'cpuscreen', 'floor', 'ceiling', 'desk', 'bedroom', 'keyboard', 'computer', 'ceilinglamp', 'mat', 'shower', 'faucet', 'window', 'mousepad', 'food_orange', 'wall', 'television', 'curtain', 'after_shave', 'mouse', 'dresser', 'door', 'napkin', 'table']
Task:Clean screen
response:
| {
"thoughts": "Use a soft rag to wipe the screen until there are no marks on it.",
"actions": [
"[WALK] <home_office>",
"[WALK] <rag>",
"[FIND] <rag>",
"[GRAB] <rag>",
"[WALK] <computer>",
"[WIPE] <computer>",
"[PUTOBJBACK] <rag>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'microwave', 'detergent', 'knifeblock', 'bathroom_counter', 'floor', 'ceiling', 'character', 'stamp', 'keyboard', 'toaster', 'plate', 'faucet', 'tvstand', 'bowl', 'wall', 'oven', 'photoframe', 'coffe_maker', 'food_food', 'ice', 'curtain', 'shaving_cream', 'kitchen_counter', 'shoes', 'dishrack', 'cupboard', 'sink', 'bathroom_cabinet', 'dishwasher']
Task:Wash dishes with dishwasher
response:
{
"thoughts": Walk to the kitchen. Open the dishwasher and turn on the faucet. Rinse off the dishes. Put the dishes in the dishwasher. Put detergent in the dishwasher. Close the dishwasher. Switch on the dishwasher.,
"actions": ['[WALK] <dining_room>', '[WALK] <dishwasher>', '[FIND] <dishwasher>', '[OPEN] <dishwasher>', '[FIND] <faucet>', '[SWITCHON] <faucet>', '[FIND] <plate>', '[GRAB] <plate>', '[RINSE] <plate>', '[PUTBACK] <plate> <dishwasher>', '[FIND] <plate>', '[GRAB] <plate>', '[RINSE] <plate>', '[PUTBACK] <plate> <dishwasher>', '[FIND] <plate>', '[GRAB] <plate>', '[RINSE] <plate>', '[PUTBACK] <plate> <dishwasher>', '[FIND] <detergent>', '[GRAB] <detergent>', '[PUTBACK] <detergent> <dishwasher>', '[CLOSE] <dishwasher>', '[SWITCHON] <dishwasher>']
}
|
Scene_Objects:['chair', 'walllamp', 'blow_dryer', 'orchid', 'cpuscreen', 'bathroom_counter', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'brush', 'ceilinglamp', 'mat', 'laptop', 'mousepad', 'dining_room', 'wall', 'powersocket', 'food_food', 'oven_mitts', 'kettle', 'mouse', 'cd', 'door', 'hairdryer', 'napkin', 'sink', 'table', 'light']
Task:Wash monitor
response:
| {
"thoughts": "Clean the grime off of my monitor screen when not in use",
"actions": [
"[WALK] <home_office>",
"[WALK] <computer>",
"[FIND] <computer>",
"[TURNTO] <computer>",
"[LOOKAT] <computer>",
"[SWITCHOFF] <computer>",
"[FIND] <brush>",
"[TURNTO] <brush>",
"[LOOKAT] <brush>",
"[GRAB] <brush>",
"[WIPE] <computer>",
"[DROP] <brush>",
"[FIND] <napkin>",
"[GRAB] <napkin>",
"[WASH] <napkin>",
"[WIPE] <computer>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['food_pizza', 'tablelamp', 'toilet', 'chair', 'detergent', 'trashcan', 'orchid', 'floor', 'ceiling', 'stamp', 'man', 'bookshelf', 'purse', 'toaster', 'mat', 'oil', 'mousepad', 'nightstand', 'cup', 'photoframe', 'newspaper', 'coffe_maker', 'tray', 'curtain', 'mouse', 'headset', 'cupboard', 'door', 'bathroom_cabinet', 'dishwasher']
Task:Answer door
response:
{
"thoughts": Wait until doorbell rings, look to see who it is outside and open the door if you feel so inclined.,
"actions": ['[WALK] <home_office>', '[WALK] <man>', '[FIND] <man>', '[GREET] <man>']
}
|
Scene_Objects:['sheets', 'filing_cabinet', 'food_salt', 'measuring_cup', 'toilet', 'jelly', 'drawing', 'floor', 'phone', 'ceiling', 'character', 'bookshelf', 'alcohol', 'mat', 'shower', 'foundation', 'electric_shaver', 'mousepad', 'wall', 'toy', 'basket_for_clothes', 'photoframe', 'wine', 'dresser', 'laundry_detergent', 'food_steak', 'door', 'napkin', 'bathroom_cabinet', 'dishwasher']
Task:Pick up toys
response:
| {
"thoughts": "Pickup toys from around the room. Organize toys back into their appropriate spaces on the shelves and into the toy boxes.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <toy>",
"[FIND] <toy>",
"[GRAB] <toy>",
"[WALK] <filing_cabinet>",
"[OPEN] <filing_cabinet>",
"[PUTBACK] <toy> <filing_cabinet>",
"[CLOSE] <filing_cabinet>",
"[FIND] <toy>",
"[GRAB] <toy>",
"[WALK] <dresser>",
"[OPEN] <dresser>",
"[PUTBACK] <toy> <dresser>",
"[CLOSE] <dresser>",
"[FIND] <toy>",
"[GRAB] <toy>",
"[WALK] <filing_cabinet>",
"[OPEN] <filing_cabinet>",
"[PUTBACK] <toy> <filing_cabinet>",
"[CLOSE] <filing_cabinet>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['dog', 'food_egg', 'bathroom_counter', 'folder', 'bedroom', 'computer', 'table_cloth', 'piano_bench', 'stovefan', 'tvstand', 'faucet', 'foundation', 'homework', 'couch', 'nightstand', 'powersocket', 'oven', 'basket_for_clothes', 'cup', 'keys', 'food_food', 'mouthwash', 'after_shave', 'doorjamb', 'shoes', 'controller', 'maindoor', 'bag', 'dirt', 'coffee']
Task:Get ready to leave
response:
{
"thoughts": Get your jacket and shoes on, locate the keys off the side table, walk out the front door and secure building with keys when you leave,
"actions": ['[WALK] <home_office>', '[WALK] <shoes>', '[FIND] <shoes>', '[GRAB] <shoes>', '[PUTON] <shoes>', '[FIND] <keys>', '[GRAB] <keys>']
}
|
Scene_Objects:['dry_pasta', 'food_ice_cream', 'walllamp', 'nail_polish', 'cat', 'orchid', 'drawing', 'floor', 'ceiling', 'purse', 'alcohol', 'mail', 'table_cloth', 'mat', 'tvstand', 'ceilinglamp', 'window', 'couch', 'pillow', 'towel', 'wall', 'oven', 'cup', 'food_cheese', 'television', 'curtain', 'doorjamb', 'door', 'table', 'clothes_shirt']
Task:Straighten paintings on wall
response:
| {
"thoughts": "Go up to the painting and tilt it which ever way it is uneven until it looks straight.",
"actions": [
"[WALK] <home_office>",
"[WALK] <wall>",
"[WALK] <drawing>",
"[FIND] <drawing>",
"[TURNTO] <drawing>",
"[LOOKAT] <drawing>",
"[TOUCH] <drawing>",
"[PULL] <drawing>",
"[PUSH] <drawing>",
"[WALK] <drawing>",
"[FIND] <drawing>",
"[TURNTO] <drawing>",
"[LOOKAT] <drawing>",
"[TOUCH] <drawing>",
"[PULL] <drawing>",
"[PUSH] <drawing>",
"[WALK] <drawing>",
"[FIND] <drawing>",
"[TURNTO] <drawing>",
"[LOOKAT] <drawing>",
"[TOUCH] <drawing>",
"[PULL] <drawing>",
"[PUSH] <drawing>",
"[TURNTO] <drawing>",
"[LOOKAT] <drawing>",
"[TURNTO] <drawing>",
"[LOOKAT] <drawing>",
"[TURNTO] <drawing>",
"[LOOKAT] <drawing>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['microwave', 'toilet', 'floor', 'ceiling', 'phone', 'bedroom', 'bookshelf', 'keyboard', 'toaster', 'ceilinglamp', 'plate', 'faucet', 'shower', 'window', 'tvstand', 'pillow', 'wall', 'wall_clock', 'powersocket', 'photoframe', 'coffe_maker', 'water', 'doorjamb', 'mouse', 'kitchen_counter', 'dresser', 'cupboard', 'sink', 'light', 'table']
Task:Drink
response:
{
"thoughts": Walk to kitchen, grab a glass, walk to sink, turn on tap and pour water into glass, drink from glass.,
"actions": ['[WALK] <dining_room>', '[WALK] <cup>', '[FIND] <cup>', '[GRAB] <cup>', '[WALK] <sink>', '[WALK] <water>', '[FIND] <water>', '[GRAB] <water>', '[POUR] <water> <cup>', '[DRINK] <cup>']
}
|
Scene_Objects:['pot', 'filing_cabinet', 'food_salt', 'toilet', 'chair', 'bathroom', 'food_carrot', 'cpuscreen', 'shampoo', 'phone', 'ceiling', 'bedroom', 'desk', 'computer', 'toaster', 'shower', 'foundation', 'dustpan', 'photoframe', 'coffe_maker', 'food_rice', 'tray', 'curtain', 'doorjamb', 'console', 'cupboard', 'bathroom_cabinet', 'light', 'dishwasher', 'creditcard']
Task:Put umbrella away
response:
| {
"thoughts": "Place the umbrella in the umbrella bucket point first.",
"actions": [
"[WALK] <home_office>",
"[WALK] <mop_bucket>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['juice', 'toilet', 'chair', 'freezer', 'detergent', 'food_carrot', 'drawing', 'knifeblock', 'floor', 'ceiling', 'food_chicken', 'bedroom', 'piano_bench', 'ceilinglamp', 'mat', 'shower', 'faucet', 'oil', 'food_orange', 'wall', 'nightstand', 'powersocket', 'photoframe', 'food_food', 'check', 'doorjamb', 'vacuum_cleaner', 'door', 'table', 'light']
Task:Put groceries in Fridge
response:
{
"thoughts": Put the groceries on the table into the fridge,
"actions": ['[WALK] <dining_room>', '[WALK] <table>', '[FIND] <food_chicken>', '[GRAB] <food_chicken>', '[FIND] <freezer>', '[OPEN] <freezer>', '[PUTBACK] <food_chicken> <freezer>', '[CLOSE] <freezer>', '[FIND] <food_carrot>', '[GRAB] <food_carrot>', '[FIND] <freezer>', '[OPEN] <freezer>', '[PUTIN] <food_carrot> <freezer>', '[CLOSE] <freezer>']
}
|
Scene_Objects:['sheets', 'pot', 'filing_cabinet', 'crayon', 'cat', 'food_butter', 'trashcan', 'bathroom_counter', 'floor', 'folder', 'mail', 'tvstand', 'window', 'mousepad', 'towel', 'wall', 'nightstand', 'bench', 'toy', 'basket_for_clothes', 'cup', 'food_cheese', 'light_bulb', 'food_food', 'television', 'curtain', 'shoes', 'dresser', 'door', 'sink']
Task:Pick up toys
response:
| {
"thoughts": "Bend down and pick up the toys off of the floor.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <toy>",
"[FIND] <toy>",
"[GRAB] <toy>",
"[WALK] <dresser>",
"[OPEN] <dresser>",
"[PUTIN] <toy> <dresser>",
"[FIND] <toy>",
"[GRAB] <toy>",
"[WALK] <dresser>",
"[PUTIN] <toy> <dresser>",
"[FIND] <toy>",
"[WALK] <dresser>",
"[GRAB] <toy>",
"[PUTIN] <toy> <dresser>",
"[CLOSE] <dresser>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['fork', 'filing_cabinet', 'food_pizza', 'knifeblock', 'food_egg', 'hanger', 'phone', 'desk', 'tea_bag', 'purse', 'envelope', 'clothes_jacket', 'table_cloth', 'faucet', 'window', 'closetdrawer', 'clothes_pants', 'food_jam', 'wall', 'basket_for_clothes', 'bed', 'cd', 'comb', 'laundry_detergent', 'clothes_scarf', 'napkin', 'home_office', 'bathroom_cabinet', 'washing_machine', 'teeth']
Task:Wash clothes
response:
{
"thoughts": Walk to bathroom. Open washing maschine. Grab pants and put it into washing maschine. Pour laundry detergent into washing machine and close the washing maschine. Plug in washing machine.,
"actions": ['[WALK] <bathroom>', '[WALK] <washing_machine>', '[FIND] <washing_machine>', '[OPEN] <washing_machine>', '[FIND] <clothes_pants>', '[GRAB] <clothes_pants>', '[PUTBACK] <clothes_pants> <washing_machine>', '[WALK] <laundry_detergent>', '[FIND] <laundry_detergent>', '[GRAB] <laundry_detergent>', '[POUR] <laundry_detergent> <washing_machine>', '[CLOSE] <washing_machine>', '[PLUGIN] <washing_machine>']
}
|
Scene_Objects:['beer', 'chair', 'band-aids', 'walllamp', 'bathroom', 'detergent', 'food_carrot', 'drawing', 'floor', 'ceiling', 'mat', 'faucet', 'mousepad', 'food_noodles', 'couch', 'wall', 'basket_for_clothes', 'photoframe', 'light_bulb', 'novel', 'television', 'coffee_filter', 'tray', 'diary', 'mouse', 'pencil', 'cd', 'chessboard', 'bathroom_cabinet', 'creditcard']
Task:Wipe down baseboards please
response:
| {
"thoughts": "Use a rag to get all the dust off the baseboards please.",
"actions": [
"[WALK] <home_office>",
"[WALK] <rag>",
"[FIND] <rag>",
"[GRAB] <rag>",
"[WALK] <wall>",
"[PUTOBJBACK] <rag>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['tablelamp', 'toilet', 'chair', 'trashcan', 'ceilingfan', 'drawing', 'cpuscreen', 'floor', 'ceiling', 'phone', 'desk', 'bedroom', 'keyboard', 'bookshelf', 'computer', 'alcohol', 'ceilinglamp', 'balanceball', 'mousepad', 'wall', 'nightstand', 'food_cheese', 'toothbrush_holder', 'doorjamb', 'towel_rack', 'mouse', 'cupboard', 'bathroom_cabinet', 'light', 'home_office']
Task:Work
response:
{
"thoughts": Type on a computer in the home office.,
"actions": ['[WALK] <home_office>', '[WALK] <computer>', '[FIND] <computer>', '[SWITCHON] <computer>', '[FIND] <keyboard>', '[TYPE] <keyboard>']
}
|
Scene_Objects:['walllamp', 'food_carrot', 'drawing', 'orchid', 'food_egg', 'bathroom_counter', 'floor', 'phone', 'character', 'desk', 'bookshelf', 'stovefan', 'ceilinglamp', 'shower', 'faucet', 'window', 'oil', 'couch', 'clothes_pants', 'pillow', 'wall', 'tape', 'cup', 'novel', 'tray', 'curtain', 'mouse', 'chessboard', 'controller', 'table']
Task:Read book
response:
| {
"thoughts": "Sit on a couch, grab a book, open it, and scan the pages",
"actions": [
"[WALK] <home_office>",
"[WALK] <novel>",
"[FIND] <novel>",
"[GRAB] <novel>",
"[WALK] <couch>",
"[SIT] <couch>",
"[TURNTO] <novel>",
"[LOOKAT] <novel>",
"[READ] <novel>",
"[READ] <novel>",
"[READ] <novel>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['ground_coffee', 'nail_polish', 'ceilingfan', 'drawing', 'knifeblock', 'cpuscreen', 'floor', 'ceiling', 'phone', 'remote_control', 'computer', 'button', 'mail', 'ceilinglamp', 'tvstand', 'balanceball', 'shower', 'window', 'couch', 'pillow', 'dining_room', 'wall', 'bench', 'tape', 'television', 'curtain', 'food_onion', 'cupboard', 'table', 'shoe_rack']
Task:Watch TV
response:
{
"thoughts": Go to the living room, sit on the couch, find the remote, switch on the TV and watch,
"actions": ['[WALK] <home_office>', '[WALK] <couch>', '[FIND] <couch>', '[SIT] <couch>', '[FIND] <remote_control>', '[FIND] <television>', '[SWITCHON] <television>', '[TURNTO] <television>', '[WATCH] <television>']
}
|
Scene_Objects:['pot', 'food_bread', 'food_ice_cream', 'tea', 'walllamp', 'drawing', 'bills', 'knifeblock', 'orchid', 'bathroom_counter', 'floor', 'keyboard', 'bookshelf', 'envelope', 'computer', 'ceilinglamp', 'iron', 'window', 'couch', 'pillow', 'wall', 'powersocket', 'oven', 'toy', 'television', 'tray', 'curtain', 'sink', 'bathroom_cabinet', 'table']
Task:Read magazine
response:
| {
"thoughts": "Please sit on the couch and read a magazine",
"actions": [
"[WALK] <home_office>",
"[WALK] <newspaper>",
"[FIND] <newspaper>",
"[GRAB] <newspaper>",
"[WALK] <couch>",
"[SIT] <couch>",
"[TURNTO] <newspaper>",
"[LOOKAT] <newspaper>",
"[READ] <newspaper>",
"[READ] <newspaper>",
"[READ] <newspaper>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['microwave', 'toilet', 'ground_coffee', 'bathroom', 'trashcan', 'food_butter', 'knifeblock', 'needle', 'floor', 'ceiling', 'character', 'clothes_jacket', 'toaster', 'ceilinglamp', 'balanceball', 'mousepad', 'broom', 'wall', 'pasta', 'photoframe', 'coffe_maker', 'coffee_filter', 'water', 'rag', 'coffee_pot', 'laundry_detergent', 'maindoor', 'napkin', 'table', 'dishwasher']
Task:Make coffee
response:
{
"thoughts": Walk to Kitchen and find coffee maker, find coffee filter and place it in coffee maker. Find ground coffee and water. put both in coffee maker. Close the coffee maker and switch it on.,
"actions": ['[WALK] <dining_room>', '[WALK] <coffe_maker>', '[FIND] <coffe_maker>', '[OPEN] <coffe_maker>', '[FIND] <coffee_filter>', '[GRAB] <coffee_filter>', '[PUTBACK] <coffee_filter> <coffe_maker>', '[FIND] <ground_coffee>', '[GRAB] <ground_coffee>', '[PUTBACK] <ground_coffee> <coffe_maker>', '[WALK] <water>', '[FIND] <water>', '[GRAB] <water>', '[POUR] <water> <coffe_maker>', '[CLOSE] <coffe_maker>', '[SWITCHON] <coffe_maker>']
}
|
Scene_Objects:['pot', 'food_pizza', 'jelly', 'chair', 'freezer', 'nail_polish', 'milk', 'hanger', 'floor', 'phone', 'ceiling', 'clothes_jacket', 'piano_bench', 'window', 'oil', 'wall', 'cup', 'keys', 'food_food', 'curtain', 'doorjamb', 'cards', 'pencil', 'vacuum_cleaner', 'dresser', 'pajamas', 'hairdryer', 'door', 'bag', 'bathroom_cabinet']
Task:Vacuum
response:
| {
"thoughts": "Plug in the vacuum. Turn it on. Push it back and forth across the floor until all the debris is gone.",
"actions": [
"[WALK] <home_office>",
"[WALK] <dresser>",
"[OPEN] <dresser>",
"[FIND] <vacuum_cleaner>",
"[GRAB] <vacuum_cleaner>",
"[PULL] <vacuum_cleaner>",
"[PLUGIN] <vacuum_cleaner>",
"[SWITCHON] <vacuum_cleaner>",
"[PULL] <vacuum_cleaner>",
"[PUSH] <vacuum_cleaner>",
"[PULL] <vacuum_cleaner>",
"[PUSH] <vacuum_cleaner>",
"[PULL] <vacuum_cleaner>",
"[PUSH] <vacuum_cleaner>",
"[SWITCHOFF] <vacuum_cleaner>",
"[PLUGOUT] <vacuum_cleaner>",
"[WALK] <dresser>",
"[PUTIN] <vacuum_cleaner> <dresser>",
"[CLOSE] <dresser>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'juice', 'blow_dryer', 'walllamp', 'detergent', 'floor', 'ceiling', 'bedroom', 'keyboard', 'purse', 'tvstand', 'deck_of_cards', 'clothes_pants', 'dining_room', 'wall', 'nightstand', 'powersocket', 'oven', 'keys', 'tray', 'kettle', 'shoes', 'hair', 'sink', 'home_office', 'table', 'dishwasher', 'soap', 'board_game', 'dirt']
Task:Hang up car keys
response:
{
"thoughts": Open the front door. Enter the entrance hall. Take out car keys from purse. Hang car keys up on hook on the wall.,
"actions": ['[WALK] <home_office>', '[WALK] <purse>', '[FIND] <purse>', '[OPEN] <purse>', '[FIND] <keys>', '[GRAB] <keys>', '[CLOSE] <purse>']
}
|
Scene_Objects:['dry_pasta', 'food_bread', 'freezer', 'food_carrot', 'milk', 'cpuscreen', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'piano_bench', 'ceilinglamp', 'mousepad', 'garbage_can', 'clothes_hat', 'food_orange', 'food_dessert', 'wall', 'powersocket', 'food_vegetable', 'food_cheese', 'doorjamb', 'lighter', 'mouse', 'coffee', 'door', 'light', 'colander', 'teeth']
Task:Rotate stock in refrigerator
response:
| {
"thoughts": "Throw out expired items, put older items in front.",
"actions": [
"[WALK] <freezer>",
"[OPEN] <freezer>",
"[FIND] <food_bread>",
"[GRAB] <food_bread>",
"[TURNTO] <food_bread>",
"[LOOKAT] <food_bread>",
"[PUTOBJBACK] <food_bread>",
"[FIND] <food_cheese>",
"[GRAB] <food_cheese>",
"[TURNTO] <food_cheese>",
"[LOOKAT] <food_cheese>",
"[FIND] <garbage_can>",
"[PUTBACK] <food_cheese> <garbage_can>",
"[FIND] <food_cheese>",
"[GRAB] <food_cheese>",
"[TURNTO] <food_cheese>",
"[LOOKAT] <food_cheese>",
"[PUTOBJBACK] <food_cheese>",
"[FIND] <food_dessert>",
"[TURNTO] <food_dessert>",
"[LOOKAT] <food_dessert>",
"[PUSH] <food_dessert>",
"[FIND] <food_vegetable>",
"[GRAB] <food_vegetable>",
"[TURNTO] <food_vegetable>",
"[LOOKAT] <food_vegetable>",
"[PUTBACK] <food_vegetable> <garbage_can>",
"[FIND] <milk>",
"[GRAB] <milk>",
"[TURNTO] <milk>",
"[LOOKAT] <milk>",
"[PUTOBJBACK] <milk>",
"[CLOSE] <freezer>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['dry_pasta', 'food_bread', 'microwave', 'freezer', 'ground_coffee', 'dough', 'orchid', 'hanger', 'floor', 'ceiling', 'character', 'desk', 'tea_bag', 'toaster', 'faucet', 'shower', 'closetdrawer', 'wall', 'wall_clock', 'powersocket', 'oven', 'cutting_board', 'photoframe', 'coffe_maker', 'coffee_filter', 'water', 'curtain', 'kitchen_counter', 'cupboard', 'sink']
Task:Make coffee
response:
{
"thoughts": I walk to the kitchen and find the coffee machine. I open the coffee machine and pour a filter in it. I open the cupboard and grab ground coffee. I put ground coffee in the filter and water in the coffee machine. I close the coffee machine. I switch on the coffee machine and wait,
"actions": ['[WALK] <dining_room>', '[WALK] <coffe_maker>', '[FIND] <coffe_maker>', '[OPEN] <coffe_maker>', '[FIND] <coffee_filter>', '[GRAB] <coffee_filter>', '[PUTBACK] <coffee_filter> <coffe_maker>', '[FIND] <cupboard>', '[OPEN] <cupboard>', '[FIND] <ground_coffee>', '[GRAB] <ground_coffee>', '[PUTBACK] <ground_coffee> <coffe_maker>', '[WALK] <water>', '[FIND] <water>', '[GRAB] <water>', '[POUR] <water> <coffe_maker>', '[CLOSE] <coffe_maker>', '[SWITCHON] <coffe_maker>']
}
|
Scene_Objects:['spectacles', 'dog', 'detergent', 'trashcan', 'orchid', 'needle', 'bathroom_counter', 'computer', 'button', 'table_cloth', 'deck_of_cards', 'stereo', 'shower', 'floor_lamp', 'towel', 'wall', 'love_seat', 'cup', 'newspaper', 'basket_for_clothes', 'photoframe', 'food_rice', 'wooden_spoon', 'doorjamb', 'dresser', 'controller', 'door', 'napkin', 'home_office', 'clothes_skirt']
Task:Read
response:
| {
"thoughts": "Sit on an easy chair. Turn on music. Take a book and read. Turn on lamp at night.",
"actions": [
"[WALK] <home_office>",
"[WALK] <stereo>",
"[FIND] <stereo>",
"[SWITCHON] <stereo>",
"[FIND] <newspaper>",
"[GRAB] <newspaper>",
"[FIND] <love_seat>",
"[SIT] <love_seat>",
"[FIND] <floor_lamp>",
"[SWITCHON] <floor_lamp>",
"[READ] <newspaper>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['food_bread', 'food_pizza', 'tablelamp', 'microwave', 'floor', 'ceiling', 'desk', 'bookshelf', 'stovefan', 'mat', 'ceilinglamp', 'laptop', 'window', 'homework', 'oil', 'closetdrawer', 'couch', 'nightstand', 'wall', 'cup', 'bed', 'food_food', 'mouthwash', 'toothbrush_holder', 'oven_mitts', 'razor', 'food_donut', 'check', 'clothes_scarf', 'bathroom_cabinet']
Task:Go to sleep
response:
{
"thoughts": Walk to bedroom. Walk to bed, lie in bed.,
"actions": ['[WALK] <bedroom>', '[WALK] <bed>', '[LIE] <bed>']
}
|
Scene_Objects:['glue', 'crayon', 'freezer', 'nail_polish', 'food_carrot', 'milk', 'cpuscreen', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'ceilinglamp', 'tvstand', 'mousepad', 'dining_room', 'wall', 'powersocket', 'cup', 'bed', 'food_food', 'doorjamb', 'mouse', 'pajamas', 'controller', 'door', 'spoon', 'napkin', 'light', 'dirt']
Task:Get glass of milk
response:
| {
"thoughts": "Get an empty glass. Take milk from refrigerator and open it. Pour milk into glass.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <cup>",
"[FIND] <cup>",
"[GRAB] <cup>",
"[WALK] <freezer>",
"[OPEN] <freezer>",
"[FIND] <milk>",
"[GRAB] <milk>",
"[POUR] <milk> <cup>",
"[PUTOBJBACK] <milk>",
"[CLOSE] <freezer>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'chair', 'walllamp', 'bathroom', 'drawing', 'wallshelf', 'hanger', 'floor', 'ceiling', 'desk', 'remote_control', 'computer', 'clothes_jacket', 'mat', 'tvstand', 'ceilinglamp', 'picture', 'closetdrawer', 'couch', 'pillow', 'wall', 'pasta', 'photoframe', 'coffe_maker', 'television', 'doorjamb', 'cards', 'dresser', 'door', 'colander']
Task:Change TV channel
response:
{
"thoughts": I walk into the living room. I sit on the couch and grab the remote. Then I turn on the TV and change the channel.,
"actions": ['[WALK] <home_office>', '[WALK] <couch>', '[FIND] <couch>', '[SIT] <couch>', '[FIND] <remote_control>', '[GRAB] <remote_control>', '[FIND] <television>', '[SWITCHON] <television>']
}
|
Scene_Objects:['fork', 'filing_cabinet', 'tablelamp', 'toilet', 'jelly', 'walllamp', 'drawing', 'orchid', 'floor', 'ceiling', 'desk', 'remote_control', 'computer', 'ceilinglamp', 'tvstand', 'mat', 'faucet', 'window', 'mousepad', 'couch', 'pillow', 'wall', 'powersocket', 'television', 'coffee_filter', 'curtain', 'doorjamb', 'centerpiece', 'door', 'table']
Task:Watch TV
response:
| {
"thoughts": "I sit down on sofa, get the remote, turn on tv, change channel to show I want to watch",
"actions": [
"[WALK] <home_office>",
"[WALK] <couch>",
"[FIND] <couch>",
"[SIT] <couch>",
"[FIND] <remote_control>",
"[GRAB] <remote_control>",
"[FIND] <television>",
"[SWITCHON] <television>",
"[TURNTO] <television>",
"[WATCH] <television>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'tablelamp', 'food_salt', 'freezer', 'orchid', 'drawing', 'wallshelf', 'clothes_underwear', 'floor', 'phone', 'bookshelf', 'stovefan', 'pillow', 'wall', 'wall_clock', 'cutting_board', 'box', 'shelf', 'newspaper', 'bed', 'novel', 'coffe_maker', 'toilet_paper', 'wooden_spoon', 'hairbrush', 'door', 'home_office', 'table', 'light', 'vase']
Task:Read book
response:
{
"thoughts": Pick up the book, open to current page, read the words.,
"actions": ['[WALK] <home_office>', '[WALK] <novel>', '[FIND] <novel>', '[GRAB] <novel>', '[READ] <novel>']
}
|
Scene_Objects:['ironing_board', 'dry_pasta', 'food_pizza', 'beer', 'dog', 'chair', 'walllamp', 'orchid', 'cpuscreen', 'phone', 'folder', 'character', 'keyboard', 'stovefan', 'laptop', 'iron', 'picture', 'mousepad', 'microphone', 'powersocket', 'cup', 'novel', 'food_food', 'food_donut', 'wine', 'pencil', 'bag', 'table', 'soap', 'clothes_shirt']
Task:Iron shirt
response:
| {
"thoughts": "Set up an ironing board and an iron. Lay a shirt on board. Run iron over shirt until it is free of wrinkles.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <ironing_board>",
"[FIND] <ironing_board>",
"[FIND] <clothes_shirt>",
"[GRAB] <clothes_shirt>",
"[PUTBACK] <clothes_shirt> <ironing_board>",
"[FIND] <iron>",
"[GRAB] <iron>",
"[PLUGIN] <iron>",
"[PLUGOUT] <iron>",
"[PUTOBJBACK] <iron>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['spectacles', 'chair', 'walllamp', 'drawing', 'wallshelf', 'hanger', 'floor', 'ceiling', 'desk', 'bookshelf', 'remote_control', 'keyboard', 'computer', 'mat', 'tvstand', 'ceilinglamp', 'picture', 'closetdrawer', 'couch', 'pillow', 'wall', 'powersocket', 'photoframe', 'television', 'rag', 'doorjamb', 'cards', 'dresser', 'sink', 'dishwasher']
Task:Watch TV
response:
{
"thoughts": Sit on my couch directly opposite my tv , switch on my tv with the remote control and watch,
"actions": ['[WALK] <home_office>', '[WALK] <couch>', '[FIND] <couch>', '[SIT] <couch>', '[FIND] <remote_control>', '[GRAB] <remote_control>', '[FIND] <television>', '[SWITCHON] <television>', '[PUTOBJBACK] <remote_control>', '[TURNTO] <television>', '[WATCH] <television>']
}
|
Scene_Objects:['food_pizza', 'food_ice_cream', 'tea', 'knifeblock', 'drawing', 'orchid', 'bathroom_counter', 'floor', 'ceiling', 'envelope', 'alcohol', 'mat', 'faucet', 'shower', 'towel', 'wall', 'toy', 'bed', 'wooden_spoon', 'doorjamb', 'vacuum_cleaner', 'pajamas', 'laundry_detergent', 'door', 'sink', 'bathroom_cabinet', 'light', 'clothes_skirt', 'soap', 'hands_both']
Task:Hand washing
response:
| {
"thoughts": "Turn on the faucet. Soap up your hands. Then rinse under the running water of the faucet. Turn off faucet and dry hands.",
"actions": [
"[WALK] <bathroom>",
"[WALK] <sink>",
"[FIND] <faucet>",
"[SWITCHON] <faucet>",
"[FIND] <soap>",
"[GRAB] <soap>",
"[FIND] <hands_both>",
"[SCRUB] <hands_both>",
"[PUTOBJBACK] <soap>",
"[WASH] <hands_both>",
"[SWITCHOFF] <faucet>",
"[FIND] <towel>",
"[GRAB] <towel>",
"[WIPE] <hands_both>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'blender', 'food_ice_cream', 'toilet', 'walllamp', 'detergent', 'drawing', 'orchid', 'wallshelf', 'floor', 'ceiling', 'computer', 'toaster', 'mat', 'tvstand', 'laptop', 'ceilinglamp', 'brush', 'couch', 'pillow', 'dining_room', 'wall', 'child', 'oven', 'photoframe', 'bed', 'television', 'doorjamb', 'mouse', 'dishwasher']
Task:Let baby learn how to walk
response:
{
"thoughts": The baby tries to stand up and balances on the couch and there are no sharp edges so it's safe.,
"actions": ['[WALK] <home_office>', '[WALK] <child>', '[FIND] <child>', '[TOUCH] <child>', '[GREET] <child>', '[FIND] <couch>', '[TURNTO] <couch>', '[POINTAT] <couch>', '[TURNTO] <child>', '[LOOKAT] <child>']
}
|
Scene_Objects:['food_bread', 'filing_cabinet', 'tablelamp', 'scissors', 'microwave', 'chair', 'freezer', 'food_butter', 'drawing', 'knife', 'cpuscreen', 'floor', 'folder', 'desk', 'keyboard', 'computer', 'mail', 'mat', 'shower', 'mousepad', 'wall', 'nightstand', 'bed', 'ice', 'after_shave', 'doorjamb', 'mouse', 'kitchen_counter', 'food_steak', 'light']
Task:Work
response:
| {
"thoughts": "I work on my HP computer.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <laptop>",
"[FIND] <laptop>",
"[GRAB] <laptop>",
"[WALK] <bed>",
"[SIT] <bed>",
"[SWITCHON] <laptop>",
"[TURNTO] <laptop>",
"[LOOKAT] <laptop>",
"[FIND] <keyboard>",
"[TYPE] <keyboard>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'filing_cabinet', 'measuring_cup', 'mop', 'microwave', 'toilet', 'bathroom', 'drawing', 'orchid', 'floor', 'ceiling', 'bedroom', 'computer', 'piano_bench', 'ceilinglamp', 'plate', 'deck_of_cards', 'mat', 'mousepad', 'couch', 'pillow', 'wall', 'bed', 'novel', 'television', 'doorjamb', 'door', 'coffee_cup', 'table', 'light']
Task:Relax on sofa
response:
{
"thoughts": you walk to the living room, open the door, find a comfy sofa, sit on it, read a book or sip a cup of coffee and relax.,
"actions": ['[WALK] <home_office>', '[WALK] <couch>', '[FIND] <couch>', '[FIND] <coffee_cup>', '[GRAB] <coffee_cup>', '[SIT] <couch>', '[FIND] <novel>', '[GRAB] <novel>', '[READ] <novel>', '[DRINK] <coffee_cup>']
}
|
Scene_Objects:['spectacles', 'pot', 'walllamp', 'nail_polish', 'knifeblock', 'kitchen_cabinet', 'floor', 'ceiling', 'bookshelf', 'computer', 'faucet', 'oil', 'dining_room', 'wall', 'nightstand', 'oven', 'powersocket', 'toy', 'cup', 'coffee_filter', 'shaving_cream', 'kitchen_counter', 'dresser', 'cupboard', 'door', 'sink', 'home_office', 'table', 'dishwasher', 'bathroom_cabinet']
Task:Get glass of water
response:
| {
"thoughts": "Get a glass from a cabinet. Hold it under the sink and turn the cold water on. Fill the glass. Turn off the water.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <kitchen_cabinet>",
"[FIND] <kitchen_cabinet>",
"[OPEN] <kitchen_cabinet>",
"[FIND] <cup>",
"[GRAB] <cup>",
"[CLOSE] <kitchen_cabinet>",
"[WALK] <sink>",
"[FIND] <faucet>",
"[SWITCHON] <faucet>",
"[PUTBACK] <cup> <sink>",
"[GRAB] <cup>",
"[SWITCHOFF] <faucet>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['spectacles', 'pot', 'tablelamp', 'chair', 'dog', 'walllamp', 'ceilingfan', 'knifeblock', 'needle', 'bathroom_counter', 'floor', 'computer', 'shoe-shine_kit', 'dustpan', 'box', 'cup', 'bed', 'keys', 'television', 'food_donut', 'tray', 'curtain', 'doorjamb', 'kettle', 'kitchen_counter', 'shoes', 'comb', 'sink', 'bathroom_cabinet', 'board_game']
Task:Brush teeth
response:
{
"thoughts": go to the bathroom and brush your teeth,
"actions": ['[WALK] <bathroom>', '[WALK] <toothbrush>', '[FIND] <toothbrush>', '[GRAB] <toothbrush>', '[WALK] <tooth_paste>', '[FIND] <tooth_paste>', '[GRAB] <tooth_paste>', '[POUR] <tooth_paste> <toothbrush>']
}
|
Scene_Objects:['pot', 'walllamp', 'toothbrush', 'knifeblock', 'orchid', 'cpuscreen', 'drawing', 'shampoo', 'floor', 'ceiling', 'desk', 'mop_bucket', 'stovefan', 'laptop', 'tvstand', 'faucet', 'wall', 'nightstand', 'oven', 'tape', 'food_food', 'tray', 'curtain', 'kettle', 'kitchen_counter', 'cupboard', 'conditioner', 'sink', 'bathroom_cabinet', 'table']
Task:Wipe down counter
response:
| {
"thoughts": "Clean counter",
"actions": [
"[WALK] <dining_room>",
"[WALK] <rag>",
"[FIND] <rag>",
"[GRAB] <rag>",
"[WALK] <sink>",
"[FIND] <faucet>",
"[SWITCHON] <faucet>",
"[RINSE] <rag>",
"[SQUEEZE] <rag>",
"[SWITCHOFF] <faucet>",
"[WALK] <kitchen_counter>",
"[WIPE] <kitchen_counter>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'tablelamp', 'chair', 'walllamp', 'drawing', 'orchid', 'cpuscreen', 'wallshelf', 'hanger', 'floor', 'phone', 'ceiling', 'desk', 'keyboard', 'computer', 'mat', 'ceilinglamp', 'tvstand', 'picture', 'mousepad', 'couch', 'pillow', 'wall', 'nightstand', 'oven', 'powersocket', 'tape', 'check', 'television', 'tray', 'doorjamb', 'towel_rack', 'mouse', 'pencil', 'comb', 'dresser', 'door', 'light']
Task:Work
response:
{
"thoughts": Walk to home office, walk to desk, sit in chair, turn on computer, look at computer, click mouse and type on keyboard.,
"actions": ['[WALK] <home_office>', '[WALK] <desk>', '[FIND] <chair>', '[SIT] <chair>', '[FIND] <computer>', '[SWITCHON] <computer>', '[TURNTO] <computer>', '[LOOKAT] <computer>', '[FIND] <mouse>', '[TOUCH] <mouse>', '[FIND] <keyboard>', '[TYPE] <keyboard>', '[TURNTO] <computer>', '[LOOKAT] <computer>']
}
|
Scene_Objects:['fork', 'food_bread', 'dog', 'ground_coffee', 'drawing', 'knifeblock', 'cpuscreen', 'floor', 'desk', 'bedroom', 'alcohol', 'mop_bucket', 'stovefan', 'laptop', 'tvstand', 'ceilinglamp', 'shoe-shine_kit', 'window', 'mat', 'mousepad', 'food_orange', 'pillow', 'powersocket', 'coffe_maker', 'fly', 'coffee_pot', 'kitchen_counter', 'cupboard', 'dishwasher', 'soap']
Task:Watch fly
response:
| {
"thoughts": "Look around for a fly, often on a wall or ceiling. Follow it's movements.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <fly>",
"[FIND] <fly>",
"[TURNTO] <fly>",
"[LOOKAT] <fly>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'ground_coffee', 'walllamp', 'knife', 'knifeblock', 'hanger', 'bathroom_counter', 'floor', 'desk', 'bedroom', 'button', 'stovefan', 'mat', 'shower', 'clothes_socks', 'pillow', 'wall', 'nightstand', 'basket_for_clothes', 'bed', 'light_bulb', 'check', 'video_game_controller', 'mouthwash', 'food_onion', 'vacuum_cleaner', 'pajamas', 'cupboard', 'hair', 'instrument_guitar']
Task:Go to sleep
response:
{
"thoughts": go to bedroom, put pajamas on, lie in bed, sleep,
"actions": ['[WALK] <bedroom>', '[WALK] <pajamas>', '[FIND] <pajamas>', '[GRAB] <pajamas>', '[PUTON] <pajamas>', '[FIND] <bed>', '[LIE] <bed>']
}
|
Scene_Objects:['filing_cabinet', 'tablelamp', 'chair', 'detergent', 'food_carrot', 'orchid', 'drawing', 'needle', 'hanger', 'floor', 'computer', 'bookmark', 'mat', 'laptop', 'faucet', 'shower', 'couch', 'candle', 'wall', 'nightstand', 'pasta', 'bed', 'photoframe', 'toilet_paper', 'toothbrush_holder', 'tray', 'kitchen_counter', 'controller', 'spoon', 'table']
Task:Read book
response:
| {
"thoughts": "I lie on my bed and read a book.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <novel>",
"[FIND] <novel>",
"[GRAB] <novel>",
"[WALK] <bed>",
"[LIE] <bed>",
"[READ] <novel>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'freezer', 'bathroom', 'food_carrot', 'drawing', 'orchid', 'wallshelf', 'food_egg', 'bathroom_counter', 'shampoo', 'phone', 'mat', 'ceilinglamp', 'shower', 'electric_shaver', 'clothes_socks', 'couch', 'microphone', 'dining_room', 'food_kiwi', 'nightstand', 'wall', 'check', 'food_food', 'after_shave', 'mouse', 'kitchen_counter', 'cupboard', 'home_office', 'laser_pointer']
Task:Turn on light
response:
{
"thoughts": I go home and it's dark so I can not see anything,
"actions": ['[WALK] <home_office>', '[WALK] <floor_lamp>', '[FIND] <floor_lamp>', '[SWITCHON] <floor_lamp>']
}
|
Scene_Objects:['filing_cabinet', 'band-aids', 'walllamp', 'drawing', 'food_egg', 'bathroom_counter', 'ceiling', 'stamp', 'desk', 'cleaning_solution', 'computer', 'stovefan', 'deck_of_cards', 'faucet', 'tvstand', 'window', 'couch', 'wall', 'nightstand', 'coffe_maker', 'television', 'mirror', 'after_shave', 'paper_towel', 'clothes_dress', 'sink', 'bag', 'bathroom_cabinet', 'dishwasher', 'laser_pointer']
Task:Clean mirror
response:
| {
"thoughts": "First spray the mirrors with Windex or window type spray. Take paper towels and wipe until sparkly clean. If they have streaks, repeat the process.",
"actions": [
"[WALK] <bathroom>",
"[WALK] <bathroom_cabinet>",
"[OPEN] <bathroom_cabinet>",
"[FIND] <paper_towel>",
"[GRAB] <paper_towel>",
"[CLOSE] <bathroom_cabinet>",
"[WALK] <mirror>",
"[FIND] <cleaning_solution>",
"[RINSE] <cleaning_solution>",
"[WIPE] <mirror>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['chair', 'freezer', 'ground_coffee', 'walllamp', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'phone', 'bedroom', 'ceilinglamp', 'tvstand', 'stereo', 'food_orange', 'cup', 'bed', 'keys', 'novel', 'food_food', 'coffe_maker', 'mouthwash', 'coin', 'check', 'diary', 'coffee_pot', 'mouse', 'dresser', 'hair', 'table', 'light']
Task:Listen to music
response:
{
"thoughts": I go to my bedroom, and then I switch on the radio,
"actions": ['[WALK] <bedroom>', '[WALK] <stereo>', '[FIND] <stereo>', '[SWITCHON] <stereo>']
}
|
Scene_Objects:['freezer', 'walllamp', 'bathroom', 'drawing', 'orchid', 'floor', 'ceiling', 'video_game_console', 'desk', 'keyboard', 'stovefan', 'ceilinglamp', 'tvstand', 'mat', 'window', 'couch', 'pillow', 'wall', 'powersocket', 'video_game_controller', 'television', 'food_rice', 'ice', 'curtain', 'doorjamb', 'dresser', 'door', 'bathroom_cabinet', 'table', 'laser_pointer']
Task:Play games
response:
| {
"thoughts": "Turn on game. Use controller",
"actions": [
"[WALK] <home_office>",
"[WALK] <television>",
"[PLUGIN] <television>",
"[SWITCHON] <television>",
"[FIND] <video_game_console>",
"[PLUGIN] <video_game_console>",
"[SWITCHON] <video_game_console>",
"[FIND] <video_game_console>",
"[FIND] <video_game_controller>",
"[GRAB] <video_game_controller>",
"[WALK] <couch>",
"[SIT] <couch>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['spectacles', 'crayon', 'microwave', 'toilet', 'knife', 'bathroom_counter', 'floor', 'ceiling', 'phone', 'shampoo', 'computer', 'mat', 'tvstand', 'picture', 'oil', 'couch', 'pillow', 'wall', 'powersocket', 'cup', 'food_food', 'tray', 'doorjamb', 'mouse', 'kitchen_counter', 'shoes', 'cupboard', 'bathroom_cabinet', 'light', 'instrument_violin']
Task:Pick up phone
response:
{
"thoughts": I walk over to the phone. .I reach my arm out. I open my hand. I place my hand on the phone. I close my fingers around the phone. I pick up the phone.,
"actions": ['[WALK] <phone>', '[TOUCH] <phone>', '[GRAB] <phone>']
}
|
Scene_Objects:['pot', 'food_pizza', 'filing_cabinet', 'microwave', 'toilet', 'dog', 'freezer', 'bathroom', 'drawing', 'cpuscreen', 'floor', 'ceiling', 'phone', 'folder', 'keyboard', 'thread', 'computer', 'mat', 'window', 'dining_room', 'wall', 'nightstand', 'bench', 'cup', 'wine', 'curtain', 'kitchen_counter', 'hairbrush', 'clothes_dress', 'food_steak']
Task:Look out window
response:
| {
"thoughts": "I head into my child's room and look out the window to view the neighborhood from a different area in the house.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <window>",
"[TURNTO] <window>",
"[LOOKAT] <window>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['glue', 'toilet', 'chair', 'walllamp', 'drawing', 'wallshelf', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'desk', 'computer', 'mail', 'mat', 'tvstand', 'ceilinglamp', 'closetdrawer', 'couch', 'pillow', 'dining_room', 'wall', 'cutting_board', 'photoframe', 'bed', 'television', 'doorjamb', 'dishrack', 'dresser', 'door', 'dishwasher']
Task:Watch TV
response:
{
"thoughts": go to the living room to watch TV,
"actions": ['[RUN] <home_office>', '[WALK] <remote_control>', '[FIND] <remote_control>', '[GRAB] <remote_control>', '[WALK] <couch>', '[SIT] <couch>', '[FIND] <television>', '[TURNTO] <television>', '[POINTAT] <television>', '[TOUCH] <remote_control>', '[SWITCHON] <television>', '[TURNTO] <television>', '[LOOKAT] <television>', '[WATCH] <television>', '[DROP] <remote_control>', '[TURNTO] <television>', '[LOOKAT] <television>', '[WATCH] <television>']
}
|
Scene_Objects:['fork', 'sheets', 'scissors', 'microwave', 'walllamp', 'bathroom', 'detergent', 'trashcan', 'toothbrush', 'floor', 'phone', 'toaster', 'mat', 'tvstand', 'dustpan', 'wall', 'box', 'photoframe', 'coffe_maker', 'check', 'oven_mitts', 'food_rice', 'curtain', 'coffee_pot', 'kitchen_counter', 'cupboard', 'hairdryer', 'dishwasher', 'soap', 'coffee']
Task:Take dishes out of dishwasher
response:
| {
"thoughts": "Take clean dishes out of the dishwasher and put away",
"actions": [
"[WALK] <dining_room>",
"[WALK] <dishwasher>",
"[OPEN] <dishwasher>",
"[CLOSE] <dishwasher>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'tablelamp', 'chair', 'walllamp', 'drawing', 'orchid', 'cpuscreen', 'wallshelf', 'hanger', 'floor', 'phone', 'ceiling', 'desk', 'keyboard', 'computer', 'mat', 'ceilinglamp', 'tvstand', 'picture', 'mousepad', 'couch', 'pillow', 'wall', 'nightstand', 'oven', 'powersocket', 'check', 'television', 'tray', 'doorjamb', 'towel_rack', 'mouse', 'dresser', 'door', 'light']
Task:Browse internet
response:
{
"thoughts": I walk into my home office and walk up to my desk. I pull out the chair and sit down. I turn on the computer. After the computer is turned on I click on the google icon. I enter Disney Cruise Line into the search bar and browse the internet.,
"actions": ['[WALK] <home_office>', '[WALK] <desk>', '[FIND] <chair>', '[PULL] <chair>', '[SIT] <chair>', '[FIND] <computer>', '[TURNTO] <computer>', '[SWITCHON] <computer>', '[FIND] <keyboard>', '[TURNTO] <keyboard>', '[LOOKAT] <keyboard>', '[TYPE] <keyboard>']
}
|
Scene_Objects:['toilet', 'chair', 'dog', 'trashcan', 'orchid', 'hanger', 'bathroom_counter', 'floor', 'ceiling', 'phone', 'stamp', 'bookshelf', 'thread', 'computer', 'food_bacon', 'brush', 'ceilinglamp', 'shower', 'window', 'mousepad', 'food_jam', 'pillow', 'wall', 'check', 'curtain', 'doorjamb', 'shoes', 'dresser', 'light', 'laser_pointer']
Task:Dust
response:
| {
"thoughts": "Using soft brush, carefully dust both Indonesian wedding doll statues.",
"actions": [
"[WALK] <home_office>",
"[WALK] <dresser>",
"[OPEN] <dresser>",
"[FIND] <brush>",
"[GRAB] <brush>",
"[CLOSE] <dresser>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['food_bread', 'blender', 'freezer', 'walllamp', 'nail_polish', 'trashcan', 'knifeblock', 'orchid', 'hanger', 'floor', 'bedroom', 'keyboard', 'computer', 'stereo', 'window', 'oil', 'couch', 'pillow', 'wall', 'cup', 'bed', 'food_donut', 'curtain', 'centerpiece', 'console', 'shoes', 'dresser', 'maindoor', 'home_office', 'light']
Task:Listen to music
response:
{
"thoughts": Turn on radio, put on favorite channel, listen to music.,
"actions": ['[WALK] <bedroom>', '[WALK] <stereo>', '[FIND] <stereo>', '[SWITCHON] <stereo>', '[FIND] <bed>', '[LIE] <bed>']
}
|
Scene_Objects:['pot', 'toilet', 'freezer', 'drawing', 'knifeblock', 'bathroom_counter', 'floor', 'ceiling', 'bookshelf', 'alcohol', 'stovefan', 'brush', 'tvstand', 'picture', 'dustpan', 'wall', 'powersocket', 'cup', 'keys', 'light_bulb', 'food_food', 'doorjamb', 'controller', 'door', 'clothes_scarf', 'bathroom_cabinet', 'light', 'dishwasher', 'home_office', 'clothes_shirt']
Task:Turn on light
response:
| {
"thoughts": "Hit light switch",
"actions": [
"[WALK] <bedroom>",
"[WALK] <light>",
"[SWITCHON] <light>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['tablelamp', 'measuring_cup', 'cd_player', 'knife', 'character', 'tea_bag', 'remote_control', 'button', 'table_cloth', 'ceilinglamp', 'shoe-shine_kit', 'shower', 'food_peanut_butter', 'candle', 'nightstand', 'bench', 'cutting_board', 'shelf', 'bed', 'photoframe', 'oven_mitts', 'food_rice', 'doorjamb', 'shaving_cream', 'mouse', 'dresser', 'controller', 'sink', 'table', 'clothes_skirt']
Task:Listen to music
response:
{
"thoughts": I walk to my living room. Find CD player. Plugin the CD player to Power. Also find the remote control. Push the Botton,
"actions": ['[WALK] <home_office>', '[WALK] <cd_player>', '[FIND] <cd_player>', '[PLUGIN] <cd_player>', '[FIND] <remote_control>', '[GRAB] <remote_control>', '[FIND] <button>', '[PUSH] <button>']
}
|
Scene_Objects:['food_salt', 'freezer', 'walllamp', 'drawing', 'floor', 'ceiling', 'bookshelf', 'mail', 'table_cloth', 'shower', 'foundation', 'dustpan', 'microphone', 'wall', 'powersocket', 'food_food', 'check', 'television', 'rag', 'doorjamb', 'kitchen_counter', 'shoes', 'cupboard', 'door', 'sink', 'hairdryer', 'light', 'clothes_skirt', 'scrabble', 'creditcard']
Task:Turn off light
response:
| {
"thoughts": "Hit the switch.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <light>",
"[SWITCHOFF] <light>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['fork', 'filing_cabinet', 'blender', 'walllamp', 'ceilingfan', 'dough', 'drawing', 'floor', 'ceiling', 'desk', 'stamp', 'remote_control', 'food_cake', 'computer', 'toaster', 'ceilinglamp', 'tvstand', 'balanceball', 'iron', 'window', 'couch', 'wall', 'oven', 'photoframe', 'novel', 'television', 'curtain', 'home_office', 'table', 'instrument_guitar']
Task:Watch TV
response:
{
"thoughts": Sit on the couch nd watch t.V,
"actions": ['[WALK] <home_office>', '[WALK] <couch>', '[FIND] <couch>', '[SIT] <couch>', '[FIND] <remote_control>', '[GRAB] <remote_control>', '[FIND] <television>', '[SWITCHON] <television>', '[TURNTO] <television>', '[LOOKAT] <television>']
}
|
Scene_Objects:['fork', 'filing_cabinet', 'food_bread', 'microwave', 'trashcan', 'drawing', 'knifeblock', 'cpuscreen', 'hanger', 'bathroom_counter', 'bedroom', 'tea_bag', 'tvstand', 'window', 'form', 'pillow', 'broom', 'bench', 'basket_for_clothes', 'newspaper', 'bed', 'check', 'coffe_maker', 'tray', 'door', 'home_office', 'light', 'bathroom_cabinet', 'tooth_paste', 'coffee']
Task:Get dressed
response:
| {
"thoughts": "I get dressed in my bedroom in the mornings.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <shoes>",
"[FIND] <shoes>",
"[GRAB] <shoes>",
"[PUTON] <shoes>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'freezer', 'detergent', 'trashcan', 'cpuscreen', 'bathroom_counter', 'floor', 'ceiling', 'phone', 'bedroom', 'desk', 'bookshelf', 'mail', 'toaster', 'ceilinglamp', 'faucet', 'window', 'pillow', 'dining_room', 'wall', 'powersocket', 'oven', 'novel', 'television', 'wooden_spoon', 'curtain', 'doorjamb', 'pencil', 'vacuum_cleaner', 'light']
Task:Turn on light
response:
{
"thoughts": switching on light in an area,
"actions": ['[WALK] <home_office>', '[WALK] <light>', '[FIND] <light>', '[SWITCHON] <light>']
}
|
Scene_Objects:['pot', 'food_pizza', 'food_ice_cream', 'chair', 'band-aids', 'toothbrush', 'orchid', 'needle', 'hanger', 'bedroom', 'desk', 'bookshelf', 'piano_bench', 'ceilinglamp', 'mat', 'clothes_socks', 'microphone', 'dining_room', 'bowl', 'nightstand', 'tray', 'curtain', 'diary', 'dresser', 'cupboard', 'spoon', 'bathroom_cabinet', 'table', 'dishwasher', 'light']
Task:Open door
response:
| {
"thoughts": "I walk up to the door. I use my hand to turn the door knob to the left. I pull the door open with the same hand I used to turn the door knob",
"actions": [
"[RUN] <home_office>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'tablelamp', 'toilet', 'walllamp', 'bathroom', 'trashcan', 'wallshelf', 'clothes_underwear', 'floor', 'desk', 'mail', 'button', 'stovefan', 'toaster', 'mousepad', 'soap', 'pillow', 'dining_room', 'photoframe', 'television', 'doorjamb', 'towel_rack', 'mouse', 'dresser', 'controller', 'bathtub', 'bathroom_cabinet', 'colander', 'clothes_shirt', 'coffee']
Task:Pet cat
response:
{
"thoughts": Find a cat in the kitchen and touch it,
"actions": ['[WALK] <dining_room>', '[WALK] <cat>', '[FIND] <cat>', '[WALK] <cat>', '[TOUCH] <cat>']
}
|
Scene_Objects:['pot', 'filing_cabinet', 'tablelamp', 'microwave', 'chair', 'band-aids', 'orchid', 'drawing', 'bathroom_counter', 'floor', 'envelope', 'computer', 'ceilinglamp', 'tvstand', 'stereo', 'form', 'wall', 'nightstand', 'powersocket', 'cup', 'bed', 'photoframe', 'coffe_maker', 'check', 'centerpiece', 'dresser', 'food_steak', 'napkin', 'tooth_paste', 'shoe_rack']
Task:Listen to music
response:
| {
"thoughts": "Put iPhone into speaker holder, open up the Pandora app, listen to music.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <phone>",
"[FIND] <phone>",
"[GRAB] <phone>",
"[WALK] <stereo>",
"[PLUGIN] <phone>",
"[SWITCHON] <stereo>",
"[FIND] <bed>",
"[SIT] <bed>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'pot', 'chair', 'freezer', 'food_carrot', 'cpuscreen', 'bathroom_counter', 'floor', 'ceiling', 'thread', 'mail', 'ceilinglamp', 'mat', 'iron', 'balanceball', 'faucet', 'food_orange', 'pillow', 'wall', 'pasta', 'box', 'cup', 'newspaper', 'food_food', 'check', 'toilet_paper', 'chessboard', 'maindoor', 'napkin', 'creditcard']
Task:Put groceries in Fridge
response:
{
"thoughts": Putting groceries in refridgerator,
"actions": ['[WALK] <dining_room>', '[WALK] <food_food>', '[FIND] <food_food>', '[GRAB] <food_food>', '[FIND] <freezer>', '[OPEN] <freezer>', '[PUTIN] <food_food> <freezer>', '[CLOSE] <freezer>']
}
|
Scene_Objects:['microwave', 'chair', 'walllamp', 'orchid', 'bills', 'cpuscreen', 'knifeblock', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'ceilinglamp', 'mat', 'mousepad', 'microphone', 'form', 'towel', 'wall', 'oven', 'food_food', 'television', 'ice', 'cards', 'mouse', 'pencil', 'cupboard', 'door', 'clothes_scarf', 'table']
Task:Clean
response:
| {
"thoughts": "Wipe down computer desk and monitor",
"actions": [
"[WALK] <home_office>",
"[WALK] <rag>",
"[FIND] <rag>",
"[GRAB] <rag>",
"[WALK] <desk>",
"[FIND] <computer>",
"[WIPE] <computer>",
"[WIPE] <desk>",
"[PUTOBJBACK] <rag>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['band-aids', 'trashcan', 'wallshelf', 'clothes_underwear', 'desk', 'keyboard', 'mail', 'computer', 'tvstand', 'shower', 'window', 'clothes_socks', 'couch', 'food_peanut_butter', 'pillow', 'basket_for_clothes', 'keys', 'coffe_maker', 'television', 'food_donut', 'tray', 'rag', 'headset', 'clothes_scarf', 'bathtub', 'sink', 'light', 'dishwasher', 'soap', 'washing_machine']
Task:Wash clothes
response:
{
"thoughts": Get dirty clothes out of basket for clothes in bedroom, carry dirty clothes to laundry room, place dirty clothes in washing machine, add laundry detergent to washing machine, turn washing machine on, set type of wash, start washing machine,
"actions": ['[WALK] <bedroom>', '[WALK] <basket_for_clothes>', '[FIND] <basket_for_clothes>', '[OPEN] <basket_for_clothes>', '[GRAB] <basket_for_clothes>', '[WALK] <bathroom>', '[WALK] <washing_machine>', '[FIND] <washing_machine>', '[OPEN] <washing_machine>', '[PUTBACK] <basket_for_clothes> <washing_machine>', '[FIND] <soap>', '[GRAB] <soap>', '[PUTBACK] <soap> <washing_machine>', '[FIND] <washing_machine>', '[CLOSE] <washing_machine>', '[SWITCHON] <washing_machine>']
}
|
Scene_Objects:['sheets', 'mop', 'bathroom', 'knife', 'hanger', 'bathroom_counter', 'ceiling', 'bedroom', 'desk', 'food_cake', 'window', 'electric_shaver', 'microphone', 'food_jam', 'dining_room', 'wall', 'photoframe', 'food_food', 'television', 'curtain', 'mouse', 'kitchen_counter', 'cd', 'chessboard', 'dresser', 'hairbrush', 'clothes_scarf', 'bathroom_cabinet', 'dishwasher', 'instrument_violin']
Task:Put on coat
response:
| {
"thoughts": "I remove my scarf from a coat peg in the entrance hall. I wrap the scarf around my neck",
"actions": [
"[WALK] <home_office>",
"[WALK] <hanger>",
"[TURNTO] <hanger>",
"[LOOKAT] <hanger>",
"[FIND] <clothes_scarf>",
"[GRAB] <clothes_scarf>",
"[PUTON] <clothes_scarf>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['food_bread', 'microwave', 'freezer', 'walllamp', 'bathroom', 'toothbrush', 'orchid', 'hanger', 'longboard', 'phone', 'desk', 'computer', 'food_bacon', 'table_cloth', 'clothes_jacket', 'brush', 'ceilinglamp', 'faucet', 'foundation', 'mousepad', 'clothes_pants', 'pasta', 'light_bulb', 'toothbrush_holder', 'coin', 'coffee_filter', 'towel_rack', 'hair', 'vase', 'tooth_paste']
Task:Wash teeth
response:
{
"thoughts": WALK TO THE BATHROOM USE PASTE AND BRUSH TO WASH YOUR TEETH,
"actions": ['[WALK] <bathroom>', '[WALK] <toothbrush_holder>', '[FIND] <toothbrush_holder>', '[FIND] <tooth_paste>', '[GRAB] <tooth_paste>', '[FIND] <toothbrush>', '[GRAB] <toothbrush>']
}
|
Scene_Objects:['tablelamp', 'toilet', 'jelly', 'chair', 'trashcan', 'woman', 'orchid', 'bathroom_counter', 'thread', 'mail', 'toaster', 'mousepad', 'clothes_socks', 'candle', 'towel', 'dining_room', 'broom', 'pasta', 'powersocket', 'oven', 'food_food', 'after_shave', 'pencil', 'hair', 'hairdryer', 'door', 'napkin', 'home_office', 'colander', 'shoe_rack']
Task:Greet guests
response:
| {
"thoughts": "Greet people into my home",
"actions": [
"[WALK] <home_office>",
"[WALK] <woman>",
"[FIND] <woman>",
"[GREET] <woman>",
"[FIND] <woman>",
"[GREET] <woman>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'tablelamp', 'chair', 'walllamp', 'drawing', 'orchid', 'cpuscreen', 'wallshelf', 'hanger', 'floor', 'phone', 'ceiling', 'desk', 'keyboard', 'computer', 'mat', 'ceilinglamp', 'tvstand', 'picture', 'mousepad', 'couch', 'pillow', 'wall', 'nightstand', 'oven', 'powersocket', 'television', 'tray', 'doorjamb', 'towel_rack', 'mouse', 'pencil', 'dresser', 'door', 'light']
Task:Write an email
response:
{
"thoughts": I need to write an e-mail to my boss about the meeting at work tomorrow.,
"actions": ['[WALK] <home_office>', '[WALK] <desk>', '[FIND] <keyboard>', '[GRAB] <keyboard>', '[OPEN] <desk>', '[PUTBACK] <keyboard> <desk>', '[FIND] <mouse>', '[GRAB] <mouse>', '[FIND] <mousepad>', '[PUTBACK] <mouse> <mousepad>', '[PLUGIN] <keyboard>', '[PLUGIN] <mouse>', '[FIND] <computer>', '[SWITCHON] <computer>', '[FIND] <chair>', '[SIT] <chair>', '[TURNTO] <computer>', '[LOOKAT] <computer>', '[TYPE] <keyboard>', '[GRAB] <mouse>', '[TOUCH] <mouse>', '[TURNTO] <computer>', '[LOOKAT] <computer>']
}
|
Scene_Objects:['microwave', 'walllamp', 'bathroom', 'detergent', 'food_carrot', 'orchid', 'drawing', 'cpuscreen', 'food_egg', 'hanger', 'bathroom_counter', 'floor', 'ceiling', 'brush', 'ceilinglamp', 'tvstand', 'mat', 'stereo', 'window', 'couch', 'pillow', 'wall', 'powersocket', 'basket_for_clothes', 'television', 'curtain', 'doorjamb', 'door', 'sink', 'table']
Task:Watch TV
response:
| {
"thoughts": "I sit on my couch and watch TV in my living room",
"actions": [
"[WALK] <home_office>",
"[WALK] <television>",
"[SWITCHON] <television>",
"[TURNTO] <television>",
"[LOOKAT] <television>",
"[TOUCH] <television>",
"[TURNTO] <television>",
"[LOOKAT] <television>",
"[TOUCH] <television>",
"[TURNTO] <television>",
"[LOOKAT] <television>",
"[WALK] <couch>",
"[SIT] <couch>",
"[TURNTO] <television>",
"[LOOKAT] <television>",
"[WATCH] <television>",
"[WATCH] <television>",
"[WATCH] <television>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['toilet', 'cat', 'ceilingfan', 'food_butter', 'drawing', 'longboard', 'floor', 'ceiling', 'shampoo', 'remote_control', 'ceilinglamp', 'tvstand', 'balanceball', 'stereo', 'window', 'couch', 'clothes_pants', 'wall', 'wall_clock', 'bench', 'television', 'curtain', 'kettle', 'towel_rack', 'hair', 'pajamas', 'maindoor', 'home_office', 'table', 'vase']
Task:Change TV channel
response:
{
"thoughts": Changing channel,
"actions": ['[WALK] <home_office>', '[WALK] <television>', '[FIND] <television>', '[SWITCHON] <television>', '[FIND] <couch>', '[SIT] <couch>', '[FIND] <remote_control>', '[GRAB] <remote_control>', '[TURNTO] <television>', '[POINTAT] <television>', '[DROP] <remote_control>']
}
|
Scene_Objects:['filing_cabinet', 'toilet', 'chair', 'ground_coffee', 'detergent', 'drawing', 'clothes_underwear', 'hanger', 'floor', 'bookshelf', 'envelope', 'mat', 'shower', 'faucet', 'homework', 'mousepad', 'wall', 'toy', 'photoframe', 'check', 'coffee_filter', 'food_onion', 'shaving_cream', 'cards', 'mouse', 'dresser', 'hairbrush', 'door', 'soap', 'scrabble']
Task:Clean
response:
| {
"thoughts": "Enter inside kid's room, begin picking up toys from the floor and putting them in a toy box, leave once once.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <toy>",
"[FIND] <toy>",
"[GRAB] <toy>",
"[WALK] <filing_cabinet>",
"[OPEN] <filing_cabinet>",
"[PUTBACK] <toy> <filing_cabinet>",
"[FIND] <toy>",
"[GRAB] <toy>",
"[WALK] <filing_cabinet>",
"[PUTBACK] <toy> <filing_cabinet>",
"[FIND] <toy>",
"[GRAB] <toy>",
"[WALK] <filing_cabinet>",
"[PUTBACK] <toy> <filing_cabinet>",
"[CLOSE] <filing_cabinet>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['microwave', 'walllamp', 'dough', 'drawing', 'orchid', 'cpuscreen', 'food_egg', 'hanger', 'floor', 'keyboard', 'bookshelf', 'food_bacon', 'ceilinglamp', 'window', 'couch', 'pillow', 'wall', 'cup', 'novel', 'check', 'curtain', 'doorjamb', 'diary', 'pencil', 'kitchen_counter', 'bag', 'home_office', 'table', 'dishwasher', 'soap']
Task:Relax on sofa
response:
{
"thoughts": move to living room, locate sofa, move to sofa, sit on sofa, lie on sofa,
"actions": ['[WALK] <home_office>', '[WALK] <couch>', '[FIND] <couch>', '[WALK] <couch>', '[SIT] <couch>', '[LIE] <couch>']
}
|
Scene_Objects:['tablelamp', 'microwave', 'toilet', 'food_carrot', 'knife', 'drawing', 'bills', 'floor', 'desk', 'computer', 'food_bacon', 'bookmark', 'homework', 'candle', 'dining_room', 'wall', 'nightstand', 'toy', 'basket_for_clothes', 'bed', 'check', 'coffe_maker', 'television', 'mouse', 'hair', 'controller', 'conditioner', 'sink', 'spoon', 'home_office']
Task:Breakfast
response:
| {
"thoughts": "I have breakfast in bed, watching tv.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <food_food>",
"[GRAB] <food_food>",
"[WALK] <bedroom>",
"[WALK] <television>",
"[SWITCHON] <television>",
"[WALK] <bed>",
"[LIE] <bed>",
"[TURNTO] <television>",
"[WATCH] <television>",
"[EAT] <food_food>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sponge', 'water_glass', 'pot', 'glue', 'walllamp', 'trashcan', 'knifeblock', 'ceiling', 'clothes_jacket', 'stovefan', 'toaster', 'mat', 'faucet', 'microphone', 'wall', 'cup', 'bed', 'food_food', 'check', 'water', 'food_donut', 'curtain', 'kitchen_counter', 'chessboard', 'cupboard', 'laundry_detergent', 'sink', 'spoon', 'bathroom_cabinet', 'dirt']
Task:Drink
response:
{
"thoughts": I walk to the kitchen. open the cupboard. Find the water glass, grab it. Fill the glass with water and drink water.,
"actions": ['[WALK] <dining_room>', '[WALK] <cupboard>', '[FIND] <cupboard>', '[OPEN] <cupboard>', '[FIND] <water_glass>', '[GRAB] <water_glass>', '[WALK] <water>', '[FIND] <water>', '[GRAB] <water>', '[POUR] <water> <water_glass>', '[DRINK] <water_glass>']
}
|
Scene_Objects:['walllamp', 'nail_polish', 'bathroom', 'detergent', 'knife', 'cpuscreen', 'dvd_player', 'bedroom', 'computer', 'table_cloth', 'mop_bucket', 'brush', 'toaster', 'shower', 'window', 'couch', 'dining_room', 'wall', 'pasta', 'cup', 'photoframe', 'after_shave', 'pencil', 'kitchen_counter', 'dresser', 'clothes_dress', 'sink', 'instrument_guitar', 'light', 'creditcard']
Task:Sit
response:
| {
"thoughts": "We sit at the dining room table",
"actions": [
"[WALK] <dining_room>",
"[WALK] <chair>",
"[FIND] <chair>",
"[PULL] <chair>",
"[SIT] <chair>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['spectacles', 'food_salt', 'chair', 'jelly', 'walllamp', 'milk', 'floor', 'bedroom', 'keyboard', 'button', 'plate', 'tvstand', 'shower', 'window', 'dustpan', 'dining_room', 'nightstand', 'oven', 'basket_for_clothes', 'check', 'coffe_maker', 'tray', 'controller', 'clothes_dress', 'food_steak', 'napkin', 'soap', 'clothes_shirt', 'scrabble', 'washing_machine']
Task:Wash clothes
response:
{
"thoughts": Walk to Bathroom. Find basket for clothes. Lift clothes dress from basket. Find washing machine. Walk to washing machine. Put clothes in washing machine. Put soap in washing machine. Switch on washing machine.,
"actions": ['[WALK] <bathroom>', '[WALK] <basket_for_clothes>', '[FIND] <basket_for_clothes>', '[FIND] <clothes_dress>', '[GRAB] <clothes_dress>', '[FIND] <washing_machine>', '[WALK] <washing_machine>', '[OPEN] <washing_machine>', '[PUTBACK] <clothes_dress> <washing_machine>', '[FIND] <soap>', '[GRAB] <soap>', '[PUTBACK] <soap> <washing_machine>', '[CLOSE] <washing_machine>', '[SWITCHON] <washing_machine>']
}
|
Scene_Objects:['spectacles', 'pot', 'filing_cabinet', 'crayon', 'toilet', 'ground_coffee', 'drawing', 'bills', 'cpuscreen', 'clothes_underwear', 'orchid', 'floor', 'phone', 'ceiling', 'bookshelf', 'mat', 'shower', 'foundation', 'homework', 'dining_room', 'wall', 'tape', 'cutting_board', 'photoframe', 'newspaper', 'food_food', 'toothbrush_holder', 'curtain', 'kitchen_counter', 'soap']
Task:Put clothes away
response:
| {
"thoughts": "I take clean clothes and either place them in dresser drawers or hang them in a closet.",
"actions": [
"[WALK] <bedroom>",
"[WALK] <filing_cabinet>",
"[OPEN] <filing_cabinet>",
"[CLOSE] <filing_cabinet>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['tablelamp', 'cd_player', 'walllamp', 'trashcan', 'food_carrot', 'drawing', 'needle', 'bathroom_counter', 'dvd_player', 'bedroom', 'bookshelf', 'alcohol', 'piano_bench', 'bookmark', 'laptop', 'stereo', 'couch', 'pillow', 'broom', 'bench', 'basket_for_clothes', 'mouse', 'shoes', 'headset', 'food_steak', 'sink', 'hairdryer', 'instrument_guitar', 'door', 'bag']
Task:Listen to music
response:
{
"thoughts": Find the playback device you want to listen to. turn on. press play. enjoyu music.,
"actions": ['[WALK] <bedroom>', '[WALK] <cd_player>', '[FIND] <cd_player>', '[SWITCHON] <cd_player>']
}
|
Scene_Objects:['food_bread', 'food_salt', 'beer', 'walllamp', 'drawing', 'orchid', 'knifeblock', 'clothes_underwear', 'floor', 'folder', 'man', 'computer', 'toaster', 'ceilinglamp', 'stereo', 'window', 'homework', 'mousepad', 'couch', 'microphone', 'pillow', 'wall', 'nightstand', 'keys', 'food_food', 'wooden_spoon', 'curtain', 'doorjamb', 'hair', 'table']
Task:Have conversation with boyfriend
response:
| {
"thoughts": "Sit on sofa, talk",
"actions": [
"[WALK] <home_office>",
"[WALK] <couch>",
"[FIND] <couch>",
"[WALK] <couch>",
"[SIT] <couch>",
"[FIND] <man>",
"[GREET] <man>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'toilet', 'chair', 'freezer', 'detergent', 'orchid', 'food_egg', 'bathroom_counter', 'floor', 'ceiling', 'character', 'bedroom', 'purse', 'toaster', 'mat', 'faucet', 'iron', 'mousepad', 'wall', 'powersocket', 'cup', 'coffe_maker', 'water', 'shaving_cream', 'kitchen_counter', 'cupboard', 'food_steak', 'sink', 'clothes_scarf', 'colander']
Task:Drink
response:
{
"thoughts": I go in the kitchen and get the glass near the sink. I open the faucet, then I pour water in it, turn off the faucet and drink it.,
"actions": ['[WALK] <dining_room>', '[WALK] <sink>', '[FIND] <cup>', '[GRAB] <cup>', '[FIND] <faucet>', '[SWITCHON] <faucet>', '[FIND] <water>', '[PUTBACK] <cup> <sink>', '[GRAB] <cup>', '[SWITCHOFF] <faucet>', '[DRINK] <cup>']
}
|
Scene_Objects:['microwave', 'chair', 'freezer', 'walllamp', 'bathroom', 'orchid', 'cpuscreen', 'clothes_underwear', 'bathroom_counter', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'mat', 'shower', 'mousepad', 'pillow', 'dining_room', 'wall', 'wall_clock', 'nightstand', 'tape', 'bed', 'console', 'mouse', 'clothes_scarf', 'light', 'soap', 'teeth']
Task:Check email
response:
| {
"thoughts": "Sit in teak deck chair, have wooden drawing board on lap, laptop on wooden drawing board, log in to my two email accounts, go through new emails and respond.",
"actions": [
"[WALK] <home_office>",
"[WALK] <laptop>",
"[FIND] <laptop>",
"[GRAB] <laptop>",
"[WALK] <chair>",
"[SIT] <chair>",
"[SWITCHON] <laptop>",
"[TURNTO] <laptop>",
"[LOOKAT] <laptop>",
"[TOUCH] <laptop>",
"[TURNTO] <laptop>",
"[LOOKAT] <laptop>",
"[TOUCH] <laptop>",
"[TURNTO] <laptop>",
"[LOOKAT] <laptop>",
"[TOUCH] <laptop>",
"[TURNTO] <laptop>",
"[LOOKAT] <laptop>",
"[TOUCH] <laptop>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['sponge', 'microwave', 'toilet', 'freezer', 'walllamp', 'knifeblock', 'cpuscreen', 'bathroom_counter', 'floor', 'ceiling', 'phone', 'bedroom', 'bookshelf', 'plate', 'faucet', 'drying_rack', 'dish_soap', 'couch', 'dining_room', 'wall', 'oven', 'newspaper', 'photoframe', 'check', 'toilet_paper', 'kitchen_counter', 'cupboard', 'sink', 'bathtub', 'table']
Task:Wash dishes by hand
response:
{
"thoughts": I walk in to the Kitchen. I find a plate, a sponge, and the dish soap. I find the faucet. I turn the faucet on. I pour water on the sponge and plate. I add dish soap to the sponge. I put the dish soap back. I scrub the plate. I rinse the plate. I place the plate on the drying rack. I rinse the sponge. I turn the faucet off.,
"actions": ['[WALK] <dining_room>', '[WALK] <faucet>', '[FIND] <faucet>', '[SWITCHON] <faucet>', '[FIND] <sponge>', '[GRAB] <sponge>', '[RINSE] <sponge>', '[FIND] <dish_soap>', '[GRAB] <dish_soap>', '[POUR] <dish_soap> <sponge>', '[PUTOBJBACK] <dish_soap>', '[FIND] <plate>', '[GRAB] <plate>', '[WASH] <plate>', '[RINSE] <plate>', '[FIND] <drying_rack>', '[PUTBACK] <plate> <plate>', '[RINSE] <sponge>', '[PUTOBJBACK] <sponge>', '[SWITCHOFF] <faucet>']
}
|
Scene_Objects:['filing_cabinet', 'crayon', 'walllamp', 'woman', 'knifeblock', 'hanger', 'ceiling', 'folder', 'character', 'man', 'mop_bucket', 'bookmark', 'shower', 'window', 'electric_shaver', 'pillow', 'dining_room', 'wall_clock', 'cutting_board', 'bed', 'television', 'wine', 'curtain', 'mouse', 'pencil', 'sink', 'home_office', 'light', 'dirt', 'shoe_rack']
Task:Greet people
response:
| {
"thoughts": "Say HI to those that come in.",
"actions": [
"[WALK] <home_office>",
"[WALK] <woman>",
"[FIND] <woman>",
"[GREET] <woman>",
"[FIND] <woman>",
"[GREET] <woman>",
"[FIND] <man>",
"[GREET] <man>",
"[FIND] <man>",
"[GREET] <man>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'tablelamp', 'beer', 'toilet', 'freezer', 'walllamp', 'drawing', 'knifeblock', 'kitchen_cabinet', 'floor', 'ceiling', 'food_chicken', 'stovefan', 'mat', 'toaster', 'shower', 'nightstand', 'wall', 'powersocket', 'oven', 'photoframe', 'food_food', 'food_donut', 'tray', 'doorjamb', 'kitchen_counter', 'cupboard', 'door', 'light', 'dishwasher']
Task:Cook some food
response:
{
"thoughts": Walk into the kitchen. Open the fridge. Take out the chicken. Open the kitchen cabinet. Take out the frying pan. Put the chicken in the frying pan. Put the frying pan on the stove. Turn on the stove. Cook the chicken.,
"actions": ['[WALK] <dining_room>', '[WALK] <freezer>', '[OPEN] <freezer>', '[FIND] <food_chicken>', '[GRAB] <food_chicken>', '[CLOSE] <freezer>', '[FIND] <kitchen_cabinet>', '[OPEN] <kitchen_cabinet>', '[FIND] <pot>', '[GRAB] <pot>', '[CLOSE] <kitchen_cabinet>', '[WALK] <oven>', '[PUTBACK] <pot> <oven>', '[PUTBACK] <food_chicken> <oven>', '[SWITCHON] <oven>']
}
|
Scene_Objects:['walllamp', 'drawing', 'orchid', 'knifeblock', 'cpuscreen', 'bathroom_counter', 'floor', 'ceiling', 'remote_control', 'ceilinglamp', 'tvstand', 'mat', 'window', 'couch', 'pillow', 'wall', 'powersocket', 'basket_for_clothes', 'food_cheese', 'television', 'curtain', 'doorjamb', 'cd', 'conditioner', 'door', 'clothes_scarf', 'home_office', 'table', 'dishwasher', 'instrument_guitar']
Task:Watch TV
response:
| {
"thoughts": "Sit on the couch nd watch t.V",
"actions": [
"[WALK] <home_office>",
"[WALK] <couch>",
"[FIND] <couch>",
"[SIT] <couch>",
"[FIND] <remote_control>",
"[GRAB] <remote_control>",
"[FIND] <television>",
"[SWITCHON] <television>",
"[TURNTO] <television>",
"[LOOKAT] <television>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['chair', 'trashcan', 'orchid', 'drawing', 'floor', 'ceiling', 'bookshelf', 'computer', 'stovefan', 'ceilinglamp', 'mat', 'shower', 'window', 'food_noodles', 'couch', 'pillow', 'wall', 'photoframe', 'toothbrush_holder', 'curtain', 'doorjamb', 'chessboard', 'door', 'bathtub', 'bag', 'home_office', 'light', 'table', 'dishwasher', 'instrument_violin']
Task:Admire art
response:
{
"thoughts": Looking at painting, art,
"actions": ['[WALK] <home_office>', '[WALK] <drawing>', '[TURNTO] <drawing>', '[LOOKAT] <drawing>', '[FIND] <drawing>', '[TURNTO] <drawing>', '[LOOKAT] <drawing>']
}
|
Scene_Objects:['glue', 'pot', 'toilet', 'chair', 'freezer', 'band-aids', 'bathroom', 'food_carrot', 'drawing', 'floor', 'mat', 'window', 'couch', 'clothes_hat', 'form', 'pillow', 'bench', 'food_food', 'check', 'coffe_maker', 'toilet_paper', 'ice', 'centerpiece', 'doorjamb', 'cupboard', 'home_office', 'table', 'light', 'bathroom_cabinet', 'scrabble']
Task:Eat dinner
response:
| {
"thoughts": "In our dining room, my family eats dinner. Once the food has been prepared, we gather at the dining room table and prepare to eat.",
"actions": [
"[WALK] <dining_room>",
"[WALK] <food_food>",
"[FIND] <food_food>",
"[GRAB] <food_food>",
"[WALK] <dining_room>",
"[WALK] <table>",
"[PUTBACK] <food_food> <table>",
"[WALK] <dining_room>",
"[WALK] <food_food>",
"[FIND] <food_food>",
"[GRAB] <food_food>",
"[WALK] <dining_room>",
"[WALK] <table>",
"[PUTBACK] <food_food> <table>",
"[WALK] <chair>",
"[PULL] <chair>",
"[SIT] <chair>",
"[TURNTO] <food_food>",
"[LOOKAT] <food_food>",
"[TURNTO] <food_food>",
"[LOOKAT] <food_food>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['food_bread', 'filing_cabinet', 'tablelamp', 'food_salt', 'toilet', 'chair', 'bathroom', 'trashcan', 'drawing', 'floor', 'character', 'desk', 'purse', 'computer', 'table_cloth', 'stovefan', 'ceilinglamp', 'tvstand', 'shower', 'foundation', 'couch', 'pillow', 'nightstand', 'powersocket', 'novel', 'tray', 'mouse', 'bathroom_cabinet', 'soap', 'teeth']
Task:Pet cat
response:
{
"thoughts": First I need to find the cat in the living room. Then I walk over to the cat and pet it gently.,
"actions": ['[WALK] <home_office>', '[WALK] <cat>', '[FIND] <cat>', '[WALK] <cat>', '[TOUCH] <cat>']
}
|
Scene_Objects:['chair', 'walllamp', 'cat', 'food_carrot', 'toothbrush', 'drawing', 'orchid', 'floor', 'mail', 'stovefan', 'ceilinglamp', 'window', 'mousepad', 'couch', 'food_jam', 'pillow', 'dining_room', 'wall', 'photoframe', 'mouthwash', 'tray', 'curtain', 'coffee_pot', 'pajamas', 'door', 'sink', 'bathroom_cabinet', 'table', 'light', 'tooth_paste']
Task:Relax
response:
| {
"thoughts": "Lie down on the couch.",
"actions": [
"[WALK] <home_office>",
"[WALK] <couch>",
"[LIE] <couch>"
]
} |
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.
Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'food_salt', 'beer', 'chair', 'freezer', 'knifeblock', 'bathroom_counter', 'longboard', 'phone', 'keyboard', 'computer', 'food_bacon', 'tvstand', 'balanceball', 'stereo', 'mousepad', 'clothes_pants', 'nightstand', 'bench', 'bed', 'photoframe', 'novel', 'television', 'pencil', 'kitchen_counter', 'vacuum_cleaner', 'food_steak', 'sink', 'hairdryer', 'vase']
Task:Read book
response:
{
"thoughts": Go to the book shelf, get a book, open the book and read the book.,
"actions": ['[WALK] <home_office>', '[WALK] <novel>', '[FIND] <novel>', '[GRAB] <novel>', '[READ] <novel>']
}
|
Scene_Objects:['dry_pasta', 'tea', 'chair', 'walllamp', 'bathroom', 'orchid', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'table_cloth', 'ceilinglamp', 'mat', 'mousepad', 'wall', 'pasta', 'powersocket', 'coffe_maker', 'doorjamb', 'mouse', 'pencil', 'kitchen_counter', 'cupboard', 'door', 'home_office', 'table', 'tooth_paste']
Task:Turn on computer
response:
| {
"thoughts": "Push power button.",
"actions": [
"[WALK] <home_office>",
"[WALK] <computer>",
"[SWITCHON] <computer>"
]
} |
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