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XR-DT: Extended Reality-Enhanced Digital Twin for Safe Motion Planning via Human-Aware Model Predictive Path Integral Control
arXiv – CS AI|Tianyi Wang, Jiseop Byeon, Ahmad Yehia, Yiming Xu, Jihyung Park, Tianyi Zeng, Sikai Chen, Ziran Wang, Junfeng Jiao, Christian Claudel|
🤖AI Summary
Researchers developed XR-DT, an Extended Reality-enhanced Digital Twin framework that combines augmented, virtual, and mixed reality to improve human-robot interaction in shared workspaces. The system uses a novel Human-Aware Model Predictive Path Integral control model with ATLAS, a Transformer-based trajectory prediction system, to enable safer and more interpretable robot navigation around humans.
Key Takeaways
- →XR-DT framework bridges physical and virtual spaces using AR, VR, and mixed reality layers for better human-robot understanding.
- →The system incorporates ATLAS, a multi-modal Transformer model for predicting human movement patterns via XR headsets.
- →Human-Aware Model Predictive Path Integral (HA-MPPI) control enables safer robot navigation in human-occupied spaces.
- →Real-world experiments demonstrated accurate human trajectory prediction and efficient robot motion planning.
- →The framework addresses the critical challenge of trust and interpretability in human-robot interaction systems.
#extended-reality#digital-twin#human-robot-interaction#transformer-model#motion-planning#xr#robotics#ai-safety#trajectory-prediction
Read Original →via arXiv – CS AI
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