Humanoid Task Efficiency Regressor (HTER)
Objective
Predict task efficiency score based on execution parameters in industrial humanoid operations.
Problem Type
Supervised Tabular Regression
Input Features
- payload_kg
- movement_distance_m
- execution_time_s
- average_joint_load
- ambient_temperature_c
Output
- predicted_efficiency_score (0-1)
Model Architecture
- Feature normalization layer
- 2 fully connected hidden layers (ReLU)
- Regression output layer (Linear)
Training Configuration
- Loss: Mean Squared Error (MSE)
- Optimizer: Adam
- Early stopping enabled
- Batch size: 32
Evaluation Metrics
- MAE
- RMSE
- R² Score
Intended Use
- Industrial process optimization
- Performance benchmarking
- Task planning calibration
License
MIT