An Improved Jump Point Search Algorithm for Home Service Robot Path Planning

Li Ma, Xiang Gao, Yingxun Fu, Dongchao Ma
{"title":"An Improved Jump Point Search Algorithm for Home Service Robot Path Planning","authors":"Li Ma, Xiang Gao, Yingxun Fu, Dongchao Ma","doi":"10.1109/CCDC.2019.8833422","DOIUrl":null,"url":null,"abstract":"When the jump point search algorithm is applied to robot path planning, there are problems such as many redundant path points, large cumulative turning angle and the robot incapable of adjusting its posture at the path point. This paper proposes an improved jump point search algorithm, which checks the connectivity between the previous point and the last point of each original point. It also uses vector cross product to identify the direction of the next path point relative to the current path point. The vector dot product is adopted to calculate the rotation angle of the current path point. Three evaluation indicators, such as the number of path points, the total path length and the cumulative turning angle, are formulated to judge the merits and demerits of the optimized algorithm. The experimental results show that on the map of scene 1, improved jump point search algorithm reduces the path points from 9 to 7, with total path length decreased by about 12%, and cumulative turning angle decreased by about 27%. The improved jump point search algorithm is designed to obtain a shorter final path, a smaller cumulative turning angle, and to able robot to adjust posture at the path point.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Chinese Control And Decision Conference (CCDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2019.8833422","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

When the jump point search algorithm is applied to robot path planning, there are problems such as many redundant path points, large cumulative turning angle and the robot incapable of adjusting its posture at the path point. This paper proposes an improved jump point search algorithm, which checks the connectivity between the previous point and the last point of each original point. It also uses vector cross product to identify the direction of the next path point relative to the current path point. The vector dot product is adopted to calculate the rotation angle of the current path point. Three evaluation indicators, such as the number of path points, the total path length and the cumulative turning angle, are formulated to judge the merits and demerits of the optimized algorithm. The experimental results show that on the map of scene 1, improved jump point search algorithm reduces the path points from 9 to 7, with total path length decreased by about 12%, and cumulative turning angle decreased by about 27%. The improved jump point search algorithm is designed to obtain a shorter final path, a smaller cumulative turning angle, and to able robot to adjust posture at the path point.
一种改进的跳跃点搜索算法用于家庭服务机器人路径规划
将跳点搜索算法应用于机器人路径规划时,存在路径点冗余多、累计转角大、机器人在路径点处无法调整姿态等问题。本文提出了一种改进的跳点搜索算法,该算法检查每个原始点的前一个点与最后一个点之间的连通性。它还使用向量叉乘来确定下一个路径点相对于当前路径点的方向。采用矢量点积计算当前路径点的旋转角度。制定了路径点数、路径总长度、累计转弯角度等3个评价指标来判断优化算法的优劣。实验结果表明,在场景1的地图上,改进的跳点搜索算法将路径点从9个减少到7个,路径总长度减少了约12%,累计转弯角度减少了约27%。改进的跳点搜索算法旨在获得更短的最终路径,更小的累计转弯角度,并能够在路径点调整机器人的姿态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信