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Cross-Domain-transfer-learning-from-Human-Motion-to-Robot-Fault-Detection

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The code trains an LSTM-based residual model on human motion data and applies transfer learning to detect robotic joint faults. It preprocesses data, maps robot features to human-like patterns, and fine-tunes a model while freezing early layers. The optimized model is evaluated with class weighting, callbacks, and feature importance analysis.

Creat2025-04-04T21:11:40
Update2025-07-14T11:22:07
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