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| import numpy as np | |
| from gym import utils | |
| from gym.envs.mujoco import MujocoEnv | |
| from gym.spaces import Box | |
| class PusherEnv(MujocoEnv, utils.EzPickle): | |
| """ | |
| ### Description | |
| "Pusher" is a multi-jointed robot arm which is very similar to that of a human. | |
| The goal is to move a target cylinder (called *object*) to a goal position using the robot's end effector (called *fingertip*). | |
| The robot consists of shoulder, elbow, forearm, and wrist joints. | |
| ### Action Space | |
| The action space is a `Box(-2, 2, (7,), float32)`. An action `(a, b)` represents the torques applied at the hinge joints. | |
| | Num | Action | Control Min | Control Max | Name (in corresponding XML file) | Joint | Unit | | |
| |-----|--------------------------------------------------------------------|-------------|-------------|----------------------------------|-------|--------------| | |
| | 0 | Rotation of the panning the shoulder | -2 | 2 | r_shoulder_pan_joint | hinge | torque (N m) | | |
| | 1 | Rotation of the shoulder lifting joint | -2 | 2 | r_shoulder_lift_joint | hinge | torque (N m) | | |
| | 2 | Rotation of the shoulder rolling joint | -2 | 2 | r_upper_arm_roll_joint | hinge | torque (N m) | | |
| | 3 | Rotation of hinge joint that flexed the elbow | -2 | 2 | r_elbow_flex_joint | hinge | torque (N m) | | |
| | 4 | Rotation of hinge that rolls the forearm | -2 | 2 | r_forearm_roll_joint | hinge | torque (N m) | | |
| | 5 | Rotation of flexing the wrist | -2 | 2 | r_wrist_flex_joint | hinge | torque (N m) | | |
| | 6 | Rotation of rolling the wrist | -2 | 2 | r_wrist_roll_joint | hinge | torque (N m) | | |
| ### Observation Space | |
| Observations consist of | |
| - Angle of rotational joints on the pusher | |
| - Angular velocities of rotational joints on the pusher | |
| - The coordinates of the fingertip of the pusher | |
| - The coordinates of the object to be moved | |
| - The coordinates of the goal position | |
| The observation is a `ndarray` with shape `(23,)` where the elements correspond to the table below. | |
| An analogy can be drawn to a human arm in order to help understand the state space, with the words flex and roll meaning the | |
| same as human joints. | |
| | Num | Observation | Min | Max | Name (in corresponding XML file) | Joint | Unit | | |
| | --- | -------------------------------------------------------- | ---- | --- | -------------------------------- | -------- | ------------------------ | | |
| | 0 | Rotation of the panning the shoulder | -Inf | Inf | r_shoulder_pan_joint | hinge | angle (rad) | | |
| | 1 | Rotation of the shoulder lifting joint | -Inf | Inf | r_shoulder_lift_joint | hinge | angle (rad) | | |
| | 2 | Rotation of the shoulder rolling joint | -Inf | Inf | r_upper_arm_roll_joint | hinge | angle (rad) | | |
| | 3 | Rotation of hinge joint that flexed the elbow | -Inf | Inf | r_elbow_flex_joint | hinge | angle (rad) | | |
| | 4 | Rotation of hinge that rolls the forearm | -Inf | Inf | r_forearm_roll_joint | hinge | angle (rad) | | |
| | 5 | Rotation of flexing the wrist | -Inf | Inf | r_wrist_flex_joint | hinge | angle (rad) | | |
| | 6 | Rotation of rolling the wrist | -Inf | Inf | r_wrist_roll_joint | hinge | angle (rad) | | |
| | 7 | Rotational velocity of the panning the shoulder | -Inf | Inf | r_shoulder_pan_joint | hinge | angular velocity (rad/s) | | |
| | 8 | Rotational velocity of the shoulder lifting joint | -Inf | Inf | r_shoulder_lift_joint | hinge | angular velocity (rad/s) | | |
| | 9 | Rotational velocity of the shoulder rolling joint | -Inf | Inf | r_upper_arm_roll_joint | hinge | angular velocity (rad/s) | | |
| | 10 | Rotational velocity of hinge joint that flexed the elbow | -Inf | Inf | r_elbow_flex_joint | hinge | angular velocity (rad/s) | | |
| | 11 | Rotational velocity of hinge that rolls the forearm | -Inf | Inf | r_forearm_roll_joint | hinge | angular velocity (rad/s) | | |
| | 12 | Rotational velocity of flexing the wrist | -Inf | Inf | r_wrist_flex_joint | hinge | angular velocity (rad/s) | | |
| | 13 | Rotational velocity of rolling the wrist | -Inf | Inf | r_wrist_roll_joint | hinge | angular velocity (rad/s) | | |
| | 14 | x-coordinate of the fingertip of the pusher | -Inf | Inf | tips_arm | slide | position (m) | | |
| | 15 | y-coordinate of the fingertip of the pusher | -Inf | Inf | tips_arm | slide | position (m) | | |
| | 16 | z-coordinate of the fingertip of the pusher | -Inf | Inf | tips_arm | slide | position (m) | | |
| | 17 | x-coordinate of the object to be moved | -Inf | Inf | object (obj_slidex) | slide | position (m) | | |
| | 18 | y-coordinate of the object to be moved | -Inf | Inf | object (obj_slidey) | slide | position (m) | | |
| | 19 | z-coordinate of the object to be moved | -Inf | Inf | object | cylinder | position (m) | | |
| | 20 | x-coordinate of the goal position of the object | -Inf | Inf | goal (goal_slidex) | slide | position (m) | | |
| | 21 | y-coordinate of the goal position of the object | -Inf | Inf | goal (goal_slidey) | slide | position (m) | | |
| | 22 | z-coordinate of the goal position of the object | -Inf | Inf | goal | sphere | position (m) | | |
| ### Rewards | |
| The reward consists of two parts: | |
| - *reward_near *: This reward is a measure of how far the *fingertip* | |
| of the pusher (the unattached end) is from the object, with a more negative | |
| value assigned for when the pusher's *fingertip* is further away from the | |
| target. It is calculated as the negative vector norm of (position of | |
| the fingertip - position of target), or *-norm("fingertip" - "target")*. | |
| - *reward_dist *: This reward is a measure of how far the object is from | |
| the target goal position, with a more negative value assigned for object is | |
| further away from the target. It is calculated as the negative vector norm of | |
| (position of the object - position of goal), or *-norm("object" - "target")*. | |
| - *reward_control*: A negative reward for penalising the pusher if | |
| it takes actions that are too large. It is measured as the negative squared | |
| Euclidean norm of the action, i.e. as *- sum(action<sup>2</sup>)*. | |
| The total reward returned is ***reward*** *=* *reward_dist + 0.1 * reward_ctrl + 0.5 * reward_near* | |
| Unlike other environments, Pusher does not allow you to specify weights for the individual reward terms. | |
| However, `info` does contain the keys *reward_dist* and *reward_ctrl*. Thus, if you'd like to weight the terms, | |
| you should create a wrapper that computes the weighted reward from `info`. | |
| ### Starting State | |
| All pusher (not including object and goal) states start in | |
| (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0). A uniform noise in the range | |
| [-0.005, 0.005] is added to the velocity attributes only. The velocities of | |
| the object and goal are permanently set to 0. The object's x-position is selected uniformly | |
| between [-0.3, 0] while the y-position is selected uniformly between [-0.2, 0.2], and this | |
| process is repeated until the vector norm between the object's (x,y) position and origin is not greater | |
| than 0.17. The goal always have the same position of (0.45, -0.05, -0.323). | |
| The default framerate is 5 with each frame lasting for 0.01, giving rise to a *dt = 5 * 0.01 = 0.05* | |
| ### Episode End | |
| The episode ends when any of the following happens: | |
| 1. Truncation: The episode duration reaches a 100 timesteps. | |
| 2. Termination: Any of the state space values is no longer finite. | |
| ### Arguments | |
| No additional arguments are currently supported (in v2 and lower), | |
| but modifications can be made to the XML file in the assets folder | |
| (or by changing the path to a modified XML file in another folder).. | |
| ``` | |
| env = gym.make('Pusher-v4') | |
| ``` | |
| There is no v3 for Pusher, unlike the robot environments where a v3 and | |
| beyond take gym.make kwargs such as xml_file, ctrl_cost_weight, reset_noise_scale etc. | |
| ### Version History | |
| * v4: all mujoco environments now use the mujoco bindings in mujoco>=2.1.3 | |
| * v2: All continuous control environments now use mujoco_py >= 1.50 | |
| * v1: max_time_steps raised to 1000 for robot based tasks (not including reacher, which has a max_time_steps of 50). Added reward_threshold to environments. | |
| * v0: Initial versions release (1.0.0) | |
| """ | |
| metadata = { | |
| "render_modes": [ | |
| "human", | |
| "rgb_array", | |
| "depth_array", | |
| ], | |
| "render_fps": 20, | |
| } | |
| def __init__(self, **kwargs): | |
| utils.EzPickle.__init__(self, **kwargs) | |
| observation_space = Box(low=-np.inf, high=np.inf, shape=(23,), dtype=np.float64) | |
| MujocoEnv.__init__( | |
| self, "pusher.xml", 5, observation_space=observation_space, **kwargs | |
| ) | |
| def step(self, a): | |
| vec_1 = self.get_body_com("object") - self.get_body_com("tips_arm") | |
| vec_2 = self.get_body_com("object") - self.get_body_com("goal") | |
| reward_near = -np.linalg.norm(vec_1) | |
| reward_dist = -np.linalg.norm(vec_2) | |
| reward_ctrl = -np.square(a).sum() | |
| reward = reward_dist + 0.1 * reward_ctrl + 0.5 * reward_near | |
| self.do_simulation(a, self.frame_skip) | |
| if self.render_mode == "human": | |
| self.render() | |
| ob = self._get_obs() | |
| return ( | |
| ob, | |
| reward, | |
| False, | |
| False, | |
| dict(reward_dist=reward_dist, reward_ctrl=reward_ctrl), | |
| ) | |
| def viewer_setup(self): | |
| assert self.viewer is not None | |
| self.viewer.cam.trackbodyid = -1 | |
| self.viewer.cam.distance = 4.0 | |
| def reset_model(self): | |
| qpos = self.init_qpos | |
| self.goal_pos = np.asarray([0, 0]) | |
| while True: | |
| self.cylinder_pos = np.concatenate( | |
| [ | |
| self.np_random.uniform(low=-0.3, high=0, size=1), | |
| self.np_random.uniform(low=-0.2, high=0.2, size=1), | |
| ] | |
| ) | |
| if np.linalg.norm(self.cylinder_pos - self.goal_pos) > 0.17: | |
| break | |
| qpos[-4:-2] = self.cylinder_pos | |
| qpos[-2:] = self.goal_pos | |
| qvel = self.init_qvel + self.np_random.uniform( | |
| low=-0.005, high=0.005, size=self.model.nv | |
| ) | |
| qvel[-4:] = 0 | |
| self.set_state(qpos, qvel) | |
| return self._get_obs() | |
| def _get_obs(self): | |
| return np.concatenate( | |
| [ | |
| self.data.qpos.flat[:7], | |
| self.data.qvel.flat[:7], | |
| self.get_body_com("tips_arm"), | |
| self.get_body_com("object"), | |
| self.get_body_com("goal"), | |
| ] | |
| ) | |