人机协作的主动运动规划
Proactive Motion Planning for Human-Robot Cooperation
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中文总结 AI 辅助
本文提出一种结合深度学习人体运动预测与静态路标图及时变A*算法的规划框架，用于UR5e机械臂的主动碰撞避免，以提升人机协作安全性。
中文摘要 AI 辅助
本摘要探讨了将人体运动预测融入主动且动态的人机感知运动规划中，旨在实现人与机器人之间的安全协作。采用一种基于图的深度学习模型来预测人体运动，并将其集成到规划框架中。该框架利用静态路标图与时变A*算法来调整UR5e机械臂的轨迹。该方法通过结合精确的运动预测与自适应轨迹规划，显著改善了人机交互，并实现了主动式碰撞避免。
英文摘要
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.
