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HAN Humanoid Balance Model v2
Overview
This model focuses on humanoid robot balance stabilization and posture correction. It processes time-series IMU and joint sensor data to predict balance adjustments.
Model Type
LSTM-based Sequential Model
Intended Use
- Balance correction
- Posture stabilization
- Fall prevention simulation
- Robotics AI research
Training Details
- Framework: PyTorch
- Epochs: 30
- Batch Size: 64
- Optimizer: Adam
- Learning Rate: 0.0005
Input
- IMU sensor data
- Joint rotation angles
- Center-of-mass metrics
Output
Balance adjustment vector
Evaluation
- Stability Accuracy: 91%
- Validation Loss: 0.11
Tags
humanoid, robotics, balance-control, lstm, han-network
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