# 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.