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Omega Humanoid AI v4
Overview
Omega Humanoid AI v4 is a high-capacity Temporal Convolution Network (TCN) combined with Transformer Encoder architecture designed for advanced humanoid motion understanding and prediction.
Model Details
- Architecture: TCN + Transformer Encoder
- Framework: PyTorch
- Tasks: Action Classification, Motion Forecasting, Balance Optimization
- Number of Classes: 12
Input Format
- Sequence Length: 120 frames
- Joints: 28
- Features per Joint: 6 (x, y, z, vx, vy, vz)
Output
- Action Label
- Confidence Score
- Future Motion Sequence
Supported Actions
- walking
- running
- jumping
- sitting
- standing
- climbing
- crouching
- grabbing_object
- throwing
- pushing
- turning_left
- turning_right
Hyperparameters
- Learning Rate: 0.0001
- Batch Size: 32
- Epochs: 100
- Optimizer: AdamW
- Dropout: 0.15
- Activation: GELU
- Loss Function: CrossEntropy + SmoothL1
Dataset
- 25,000 motion sequences
- 12 action classes
- Augmented with noise, rotation, scaling, and time distortion
License
Apache 2.0
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