人間とロボットの協調のための先読み動作計画
Proactive Motion Planning for Human-Robot Cooperation
深層学習による人間の動作予測を組み込み、時間変化対応A*でUR5eマニピュレータの軌道を動的に修正することで、安全な協調と先回りの衝突回避を実現する手法を提案した。
著者: Elena Basei, Edoardo Lamon, Matteo Saveriano, Daniele Fontanelli, Luigi Palopoli
分類: cs.RO
原文アブストラクト
This abstract addresses the incorporation of human motion prediction into proactive and dynamic human-aware motion planning, with the goal of enabling safe collaboration between humans and robots. A deep learning, graph-based model is used to forecast human motion and is integrated into a planning framework. This framework employs a static roadmap along with a time-variant A* algorithm to modify the trajectory of a UR5e manipulator. This method greatly improves human-robot interaction and enables proactive collision avoidance by combining precise motion forecasts with adaptive trajectory planning.