Human Motion Prediction for Human-Robot Collaboration
arXiv:2609.32346
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.
Presented at I-RIM 3D 2024