Humanoid Motion Smoothness Predictor (HMSP)
Objective
Predict motion smoothness score
based on joint and trajectory metrics.
Problem Type
Supervised Tabular Regression
Input Features
- joint_velocity_variance
- joint_acceleration_variance
- trajectory_deviation_cm
- step_time_variation
Output
- predicted_motion_smoothness_score
Model Architecture
- Feature normalization layer
- Two dense hidden layers (ReLU activation)
- Linear regression output layer
Training Configuration
- Loss: Mean Squared Error (MSE)
- Optimizer: Adam
- Early stopping enabled
- Batch size: 32
Evaluation Metrics
Deployment Scenario
- Real-time motion quality monitoring
- Adaptive control refinement
- Locomotion performance optimization
Limitations
- Requires structured motion metrics
- Not intended for raw sensor time-series input
License
MIT
