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Caplin43/han-humanoid-motion-v1

sourceHugging Faceupdated 7mo agoView on Hugging Face

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Model Card

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%