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README.md
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<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/67639932ad38702e6c8d16d9/V7InyG4CAh5NhUXILTK9b.mp4"></video>
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To make the motion of humanoid robots more natural, we
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This database stores the
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```txt
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The Order of Configuration
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<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/67639932ad38702e6c8d16d9/V7InyG4CAh5NhUXILTK9b.mp4"></video>
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To make the motion of humanoid robots more natural, we retargeted [LAFAN1](https://github.com/ubisoft/ubisoft-laforge-animation-dataset) motion capture data to [Unitree](https://www.unitree.com/)'s humanoid robots, supporting three models: [H1, H1_2](https://www.unitree.com/h1), and [G1](https://www.unitree.com/g1). This retargeting was achieved through numerical optimization based on [Interaction Mesh](https://ieeexplore.ieee.org/document/6651585) and IK, considering end-effector pose constraints, as well as joint position and velocity constraints, to prevent foot slippage. It is important to note that the retargeting only accounted for kinematic constraints and did not include dynamic constraints or actuator limitations. As a result, the robot cannot perfectly execute the retargeted trajectories.
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This database stores the retargeted trajectories in CSV format. Each row in the CSV file corresponds to the original motion capture data for each frame, recording the configurations of all joints in the humanoid robot in the following order:
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```txt
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The Order of Configuration
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