HAN Humanoid Motion Model v1
Overview
HAN Humanoid Motion Model v1 is designed for humanoid robot training simulations.
The model predicts next-step motion states based on joint angle sequences,
velocity inputs, and balance metrics.
Model Type
Transformer-based Time Series Prediction Model
Intended Use
- Humanoid robot motion prediction
- Robotics simulation environments
- AI robotics research
- Movement stability analysis
Training Details
- Framework: PyTorch
- Epochs: 25
- Batch Size: 32
- Optimizer: Adam
- Learning Rate: 0.0003
Input
Time-series motion sensor data:
- Joint angles
- Velocity
- Gyroscope balance metrics
Output
Predicted next movement state vector.
Evaluation Metrics
- Accuracy: 92%
- Validation Loss: 0.08
- Stability Score: 89%
Tags
humanoid, robotics, motion-control, transformer, han-network
