Human Motion Prediction for Human-Robot Collaboration

Abstract:This paper compares three human motion prediction methods - GMM-based clustering, TransFusion, and Graph-Mixer - evaluating their effectiveness in human-robot collaboration. These predictions are valuable for improving robot motion planning by anticipating human movements and enhancing safety and efficiency in dynamic environments.

Robotics (cs.RO)

arXiv:2609.32346 [cs.RO]

(or arXiv:2609.32346v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2609.32346 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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