人机协作任务在线运动规划的MPC框架

M. Faroni, M. Beschi, N. Pedrocchi
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引用次数: 23

摘要

人-机器人协作需要新的规划策略,以保证机器人和人在工作空间中高效、安全共存。我们提出了一种基于模型预测控制方法的框架,用于轨迹缩放和逆运动学。在线修改速度覆盖降低了任务速度,以确保安全,并利用系统的冗余来最大化与操作人员的距离。在一个七自由度机器人系统上的实验结果证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An MPC Framework for Online Motion Planning in Human-Robot Collaborative Tasks
Human robot collaboration requires new planning strategies to guarantee an efficient and safe coexistence of robots and humans in the workspace. We propose a framework based on a model predictive control approach to trajectory scaling and inverse kinematics. The online modification of the velocity override slows down the task to ensure safety and the redundancy of the system is exploited to maximize the distance from the operator. Experimental results on a 7-degree-of-freedom robotic system prove the effectiveness of the method.
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