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This model is designed as a base neural network architecture for humanoid robot control and motion learning. |
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- Humanoid locomotion |
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- Joint control prediction |
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- Robotics simulation and reinforcement learning |
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- Feedforward Neural Network (MLP) |
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- Suitable for imitation learning and RL fine-tuning |
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This model can be fine-tuned using humanoid robotics datasets such as: |
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- Motion capture data |
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- Joint angle trajectories |
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- Sensor-to-action mappings |
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- PyTorch |
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- Robotics / Humanoid AI |
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Base model prepared for further training and experimentation. |
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