| # HAN Humanoid Motion Control Model |
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| ## Overview |
| This model is designed for humanoid robot motion control and task execution. |
| It focuses on balance, walking patterns, and basic object interaction. |
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| ## Model Type |
| Transformer-based sequence model |
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| ## Training Data |
| - Synthetic humanoid motion dataset |
| - Reinforcement learning simulations |
| - Human motion capture samples |
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| ## Input |
| - Joint angles |
| - Sensor signals (IMU, force sensors) |
| - Task command tokens |
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| ## Output |
| - Motor control signals |
| - Motion trajectory predictions |
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| ## Framework |
| PyTorch |
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| ## Use Case |
| - Humanoid robot walking |
| - Object pickup simulation |
| - Balance recovery tasks |
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| ## License |
| MIT |
