首页> 外文会议>IEEE International Conference on Automation Science and Engineering >Miniature Robot Path Planning for Bridge Inspection: Min-Max Cycle Cover-Based Approach
【24h】

Miniature Robot Path Planning for Bridge Inspection: Min-Max Cycle Cover-Based Approach

机译:用于桥梁检查的微型机器人路径规划:基于最小最大循环覆盖的方法

获取原文

摘要

We study the problem of planning the deployments of a group of mobile robots. While the problem and formulation can be used for many different problems, here we use a bridge inspection as a motivating application for the purpose of exposition. The robots are initially stationed at a set of depots placed throughout the bridge. Each robot is then assigned a set of sites on the bridge to inspect and, upon completion, must return to the same depot where it is stored. The problem of robot planning is formulated as a rooted min-max cycle cover problem, in which the vertex set consists of the sites to be inspected and robot depots, and the weight of an edge captures either (i) the amount of time needed to travel from one end vertex to the other vertex or (ii) the necessary energy expenditure for the travel. In the first case, the objective function is the total inspection time, whereas in the latter case, it is the maximum energy expenditure among all deployed robots. We propose a novel algorithm with approximation ratio of $5+epsilon$, where $0 lt epsilon lt 1$. In addition, the computational complexity of the proposed algorithm is shown to be $O(n^{2}+2^{m-1}nlog(n)+nlog(epsilon^{-1}))$, where n is the number of vertices, and m is the number of depots.
机译:我们研究了规划一组移动机器人的部署问题。尽管该问题和公式可用于许多不同的问题,但出于说明目的,我们在这里使用桥梁检查作为激励性应用程序。机器人最初位于整个桥梁上的一组仓库中。然后,为每个机器人分配了桥上的一组站点进行检查,完成后,必须返回到存储该机器人的同一个仓库。机器人计划问题被表述为根本的最小-最大循环覆盖问题,其中顶点集由要检查的站点和机器人仓库组成,并且边缘的权重捕获(i)所需的时间量。从一个末端顶点移动到另一顶点,或(ii)行程所需的能量消耗。在第一种情况下,目标函数是总检查时间,而在后一种情况下,目标函数是所有部署的机器人中最大的能量消耗。我们提出了一种新算法,其近似比率为$ 5 + \ epsilon $,其中$ 0 \ lt \ epsilon \ lt 1 $。另外,所提出算法的计算复杂度显示为$ O(n ^ {2} + 2 ^ {m-1} n \ log(n)+ n \ log(\ epsilon ^ {-1})) $,其中n是顶点数,m是仓库数。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号