Conditional task and motion planning through an effort-based approach

Nicola Castaman, E. Tosello, E. Pagello
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引用次数: 1

Abstract

This paper proposes a preliminary work on a Conditional Task and Motion Planning algorithm able to find a plan that minimizes robot efforts while solving assigned tasks. Unlike most of the existing approaches that replan a path only when it becomes unfeasible (e.g., no collision-free paths exist), the proposed algorithm takes into consideration a replanning procedure whenever an effort-saving is possible. The effort is here considered as the execution time, but it is extensible to the robot energy consumption. The computed plan is both conditional and dynamically adaptable to the unexpected environmental changes. Based on the theoretical analysis of the algorithm, authors expect their proposal to be complete and scalable. In progress experiments aim to prove this investigation.
条件任务和运动规划通过努力为基础的方法
本文提出了一种条件任务和运动规划算法的初步工作,该算法能够在解决分配的任务时找到最小化机器人努力的计划。与大多数现有方法不同的是,只有当路径变得不可行的时候才重新规划路径(例如,没有无碰撞的路径存在),该算法在可能节省努力的情况下考虑重新规划过程。这里的工作量被认为是执行时间,但它可以扩展到机器人的能量消耗。计算出的方案既具有条件性,又能动态地适应意外的环境变化。在对算法进行理论分析的基础上,作者期望他们的提议是完整的和可扩展的。正在进行的实验旨在证明这一调查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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