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Online path planning in dynamic environments using the curve shortening flow method

机译:使用曲线缩短流方法在动态环境中进行在线路径规划

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摘要

Handling tasks with robots which are interacting in a shared workspace provide a high risk of collision. A new approach based on curve shortening flows enables collision-free path planning for robots within a varying environment on basis of a workspace model. Thereby a global path planning method based on geometrical curvature flow is combined with the locally and reactively acting potential field method. In the authors' previous work this path was formulated as a non-linear partial differential equation and solved using explicit time-integration. This article presents a linearized model of this method which overcomes the numerical stability problems of the former formulation and allows a more efficient computation which is strongly required for the algorithm to be run on a realtime robot control. After a detailed explanation of the algorithm simulative and experimental results using the example of a handling task performed by two 5-axis manipulators is presented and effects of different parameter settings on the resulting path are discussed.
机译:使用在共享工作空间中进行交互的机器人来处理任务会带来很高的碰撞风险。基于曲线缩短流的新方法可以根据工作空间模型为变化环境中的机器人实现无碰撞路径规划。因此,将基于几何曲率流的全局路径规划方法与局部和反应作用的势场方法相结合。在作者先前的工作中,此路径被公式化为非线性偏微分方程,并使用显式时间积分法求解。本文介绍了该方法的线性化模型,该模型克服了以前公式的数值稳定性问题,并允许更高效的计算,这是算法在实时机器人控制上运行所强烈需要的。在以两个5轴机械手执行的处理任务为例,对算法的仿真结果和实验结果进行了详细说明之后,并讨论了不同参数设置对结果路径的影响。

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