Local minima-free design of artificial coordinating fields
Xingjian JING
Yuechao WANG
摘要：In order to overcome the drawbacks of conventional artificial potential fields (APF) based methods for the motion planning problems of mobile robots in dynamic uncertain environments,an artificial coordinating fields (ACF) based method has been proposed recently.This paper deals with the reachability problem of the ACF,that is,how to design and choose the parameters of the ACF and how the environment should be such that the robot can reach its goal without being trapped in local minima.Some sufficient conditions for these purposes are developed theoretically.Theoretical analyses show that,the ACF can effectively remove local minima in dynamic uncertain environments with V-shape or U-shape obstacles,and guide the mobile robot to reach its goal with some necessary environment constraints and based on the methods provided in this paper to properly choose the parameters of the ACF.Comparisons between the ACF and APF,and simulations are provided to illustrate the advantages of the ACF.
机标关键词：
分类号：O1(数学)
资助基金：国家自然科学基金(60131160741)国家自然科学基金(60334010)
论文发表日期：2004-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：10( 371-380 )
英文信息