基于改进A*和DWA算法的机器人动态路径规划

Chenxi Guan, Shuying Wang
{"title":"基于改进A*和DWA算法的机器人动态路径规划","authors":"Chenxi Guan, Shuying Wang","doi":"10.1109/ICCR55715.2022.10053929","DOIUrl":null,"url":null,"abstract":"When the traditional A* algorithm is applied to robot path planning, it has the problems of low efficiency and unable to avoid obstacles dynamically. In order to solve the above problems, a fusion algorithm based on improved A* algorithm and DWA algorithm is proposed. The A* algorithm is improved in three aspects: reducing the search direction of A* algorithm to reduce the search time, adding path information parameters to dynamically adjust the weight of heuristic function, and introducing important node extraction strategy to reduce the number of turns and shorten the path. Finally, the improved A* algorithm is fused with DWA algorithm. The experimental results show that the improved fusion algorithm can realize global optimal path planning and local real-time obstacle avoidance.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Robot Dynamic Path Planning Based on Improved A* and DWA Algorithms\",\"authors\":\"Chenxi Guan, Shuying Wang\",\"doi\":\"10.1109/ICCR55715.2022.10053929\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"When the traditional A* algorithm is applied to robot path planning, it has the problems of low efficiency and unable to avoid obstacles dynamically. In order to solve the above problems, a fusion algorithm based on improved A* algorithm and DWA algorithm is proposed. The A* algorithm is improved in three aspects: reducing the search direction of A* algorithm to reduce the search time, adding path information parameters to dynamically adjust the weight of heuristic function, and introducing important node extraction strategy to reduce the number of turns and shorten the path. Finally, the improved A* algorithm is fused with DWA algorithm. The experimental results show that the improved fusion algorithm can realize global optimal path planning and local real-time obstacle avoidance.\",\"PeriodicalId\":441511,\"journal\":{\"name\":\"2022 4th International Conference on Control and Robotics (ICCR)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 4th International Conference on Control and Robotics (ICCR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCR55715.2022.10053929\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 4th International Conference on Control and Robotics (ICCR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCR55715.2022.10053929","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

摘要

将传统的A*算法应用于机器人路径规划时,存在效率低、不能动态避障等问题。为了解决上述问题,提出了一种基于改进a *算法和DWA算法的融合算法。对A*算法进行了三方面的改进:减小A*算法的搜索方向,减少搜索时间;增加路径信息参数,动态调整启发式函数的权重;引入重要节点提取策略,减少匝数,缩短路径。最后,将改进的A*算法与DWA算法进行融合。实验结果表明,改进的融合算法可以实现全局最优路径规划和局部实时避障。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robot Dynamic Path Planning Based on Improved A* and DWA Algorithms
When the traditional A* algorithm is applied to robot path planning, it has the problems of low efficiency and unable to avoid obstacles dynamically. In order to solve the above problems, a fusion algorithm based on improved A* algorithm and DWA algorithm is proposed. The A* algorithm is improved in three aspects: reducing the search direction of A* algorithm to reduce the search time, adding path information parameters to dynamically adjust the weight of heuristic function, and introducing important node extraction strategy to reduce the number of turns and shorten the path. Finally, the improved A* algorithm is fused with DWA algorithm. The experimental results show that the improved fusion algorithm can realize global optimal path planning and local real-time obstacle avoidance.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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