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arXiv 2609.22974cs.ROcs.AI

一种用于机器人导航的最小障碍物位移规划的水平切片方法

A Horizon-slicing Approach to Minimum Obstacle Displacement Planning for Robot Navigation

Antony Thomas, Giulio Ferro, Fulvio Mastrogiovanni, Michela Robba, Marco Baglietto

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中文总结 AI 辅助

本文研究机器人导航中的最小障碍物位移规划问题,证明其NP难,并提出一种计算强度较低、可在路径长度与障碍物位移量间权衡的近似解。

中文摘要 AI 辅助

本文从机器人运动规划的角度研究了最小障碍物位移规划问题。该问题涉及在初始不存在无碰撞路径时,通过移动可移动障碍物来确定通往目标位置的可行路径。我们证明了该问题在计算上具有挑战性,特别是当障碍物被建模为平面中的多边形时,该问题是NP难的。除了对最小障碍物位移问题(该问题推广了文献中的其他问题)的精确表述及其相关最优解之外,本文还提出了一种近似解,该解在计算上强度较低,并且与最优解的差异仅为最优成本的一小部分,能够在路径长度与障碍物位移量之间进行权衡。

英文摘要

In this paper, we investigate the Minimum Obstacle Displacement Planning problem from a robot motion planning perspective. The problem involves determining a feasible path to a goal location by displacing movable obstacles when no collision-free path initially exists. We show that this problem is computationally challenging and, in particular, NP-hard when obstacles are modeled as polygons in the plane. Besides an exact formulation of the minimum obstacle displacement problem generalizing other problems in the literature, and the associated optimal solution, this paper proposes an approximate solution that is less intensive from a computational standpoint, and differs from the optimal solution by a fraction of the optimal cost, being able to trade-off between path length and amount of obstacle displacements.

发表机构

  • IIIT Hyderabad(海得拉巴国际信息技术学院)
  • University of Genoa(热那亚大学)

机构由 AI 辅助整理,请以论文原文为准。

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