Path planning in extended uncertain environments

M. Rendas, S. Rolfes
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引用次数: 1

Abstract

This paper presents a new approach to the problem of planning the motion of a mobile robot in extended uncertain environments. All knowledge of the environment has been acquired by the robot during the current (or a previous) operation, such that the environment description reflects the accumulated error of the robot's pose during periods of dead-reckoning navigation. In this uncertain environment, the robot searches for trajectories that maximize the probability of attaining a desired target region. For that purpose we identify a discrete set of robot positions in order to construct a routing graph, whose arcs represent the probability of reaching a new position. In that way the search for an optimal trajectory is solved by searching for a minimum weight path in a routing graph. The method is based on a probabilistic model of all the errors/uncertainties affecting the reliability of the planned trajectory.
扩展不确定环境下的路径规划
本文提出了一种解决扩展不确定环境下移动机器人运动规划问题的新方法。机器人在当前(或之前)操作中获得了所有环境知识,因此环境描述反映了机器人在航位推算导航期间的姿势累积误差。在这种不确定的环境中,机器人搜索最大概率到达目标区域的轨迹。为此,我们确定了一组离散的机器人位置,以构造一个路由图,其弧线表示到达新位置的概率。这样,通过在路由图中搜索最小权值路径来求解最优轨迹的搜索。该方法基于影响规划轨迹可靠性的所有误差/不确定性的概率模型。
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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