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