基于预规划思想的改进CBS算法

Zhuoran Wang, Jiayan Wen, Jingjing Lu
{"title":"基于预规划思想的改进CBS算法","authors":"Zhuoran Wang, Jiayan Wen, Jingjing Lu","doi":"10.1117/12.2682558","DOIUrl":null,"url":null,"abstract":"The Conflict-Based Search (CBS) algorithm is one of the Multi-Agent Path Finding (MAPF) algorithms that has received much attention in recent years. It is a two-level algorithm. The high-level detects and resolves conflicts on a Constraint Tree (CT). Its low-level algorithm is to plan the optimal path for a given agent that satisfies all the constraints of the agent. In this paper, the Space-Time A* (STA*) algorithm is used as the low-level algorithm, which adds the time dimension to the A* algorithm. It means that the planning path for a single agent tends to generate and extend more and more sub-nodes. As the complexity of the problem increases, the efficiency of the low-level solution becomes an increasingly large part of the overall solution efficiency. This leads to an inefficient overall solution. To address this problem, an improved CBS algorithm is proposed. This algorithm is used when the current node in CT has conflicts. It uses current node information and Multi-value Decision Diagram (MDD) technology to pre-plan before formal re-planning. The pre-planning phase entails obtaining information pertaining to the path that satisfies the new constraint, which is referred to as pre-planning information. During the formal re-planning, the pre-planning information is used to guide the low-level algorithm to select the generated sub-nodes. The simulation experiments show that CBS with pre-planning improves the solution time by 24.4% and reduces the search space by 38.7%.","PeriodicalId":177416,"journal":{"name":"Conference on Electronic Information Engineering and Data Processing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improved CBS algorithm based on the idea of pre-planning\",\"authors\":\"Zhuoran Wang, Jiayan Wen, Jingjing Lu\",\"doi\":\"10.1117/12.2682558\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Conflict-Based Search (CBS) algorithm is one of the Multi-Agent Path Finding (MAPF) algorithms that has received much attention in recent years. It is a two-level algorithm. The high-level detects and resolves conflicts on a Constraint Tree (CT). Its low-level algorithm is to plan the optimal path for a given agent that satisfies all the constraints of the agent. In this paper, the Space-Time A* (STA*) algorithm is used as the low-level algorithm, which adds the time dimension to the A* algorithm. It means that the planning path for a single agent tends to generate and extend more and more sub-nodes. As the complexity of the problem increases, the efficiency of the low-level solution becomes an increasingly large part of the overall solution efficiency. This leads to an inefficient overall solution. To address this problem, an improved CBS algorithm is proposed. This algorithm is used when the current node in CT has conflicts. It uses current node information and Multi-value Decision Diagram (MDD) technology to pre-plan before formal re-planning. The pre-planning phase entails obtaining information pertaining to the path that satisfies the new constraint, which is referred to as pre-planning information. During the formal re-planning, the pre-planning information is used to guide the low-level algorithm to select the generated sub-nodes. The simulation experiments show that CBS with pre-planning improves the solution time by 24.4% and reduces the search space by 38.7%.\",\"PeriodicalId\":177416,\"journal\":{\"name\":\"Conference on Electronic Information Engineering and Data Processing\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference on Electronic Information Engineering and Data Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2682558\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference on Electronic Information Engineering and Data Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2682558","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

基于冲突的搜索(CBS)算法是近年来备受关注的多智能体寻径算法之一。它是一个两级算法。高层在约束树(CT)上检测和解决冲突。其底层算法是为给定的智能体规划满足其所有约束的最优路径。本文采用时空A* (STA*)算法作为底层算法,在A*算法的基础上增加了时间维度。这意味着单个代理的规划路径倾向于生成和扩展越来越多的子节点。随着问题复杂性的增加,底层解决方案的效率在整体解决方案效率中所占的比例越来越大。这将导致低效的整体解决方案。为了解决这一问题,提出了一种改进的CBS算法。该算法适用于CT中当前节点存在冲突的情况。它利用当前节点信息和多值决策图(MDD)技术在正式重新规划之前进行预规划。预规划阶段需要获取与满足新约束的路径相关的信息,这些信息被称为预规划信息。在正式重新规划时,预规划信息用于指导底层算法选择生成的子节点。仿真实验表明,采用预先规划的CBS算法,求解时间提高了24.4%,搜索空间减少了38.7%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved CBS algorithm based on the idea of pre-planning
The Conflict-Based Search (CBS) algorithm is one of the Multi-Agent Path Finding (MAPF) algorithms that has received much attention in recent years. It is a two-level algorithm. The high-level detects and resolves conflicts on a Constraint Tree (CT). Its low-level algorithm is to plan the optimal path for a given agent that satisfies all the constraints of the agent. In this paper, the Space-Time A* (STA*) algorithm is used as the low-level algorithm, which adds the time dimension to the A* algorithm. It means that the planning path for a single agent tends to generate and extend more and more sub-nodes. As the complexity of the problem increases, the efficiency of the low-level solution becomes an increasingly large part of the overall solution efficiency. This leads to an inefficient overall solution. To address this problem, an improved CBS algorithm is proposed. This algorithm is used when the current node in CT has conflicts. It uses current node information and Multi-value Decision Diagram (MDD) technology to pre-plan before formal re-planning. The pre-planning phase entails obtaining information pertaining to the path that satisfies the new constraint, which is referred to as pre-planning information. During the formal re-planning, the pre-planning information is used to guide the low-level algorithm to select the generated sub-nodes. The simulation experiments show that CBS with pre-planning improves the solution time by 24.4% and reduces the search space by 38.7%.
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:604180095
Book学术官方微信