基于虚拟信息素的实时分布式多机器人目标跟踪

Joseph Prince Mathew, Cameron Nowzari
{"title":"基于虚拟信息素的实时分布式多机器人目标跟踪","authors":"Joseph Prince Mathew, Cameron Nowzari","doi":"10.1109/IROS47612.2022.9981262","DOIUrl":null,"url":null,"abstract":"Actively searching for targets using a multi-agent system in an unknown environment poses a two-pronged prob-lem, where on the one hand we need agents to cover as much of the environment as possible and on the other have a higher density of agents where there are potential targets to maximize detection performance. This paper proposes a fully distributed solution for an ad hoc network of agents to cooperatively search an unknown environment and actively track found targets. The solution combines a distributed pheromone-based coverage control strategy with a distributed target selection mechanism.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Real-Time Distributed Multi-Robot Target Tracking via Virtual Pheromones\",\"authors\":\"Joseph Prince Mathew, Cameron Nowzari\",\"doi\":\"10.1109/IROS47612.2022.9981262\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Actively searching for targets using a multi-agent system in an unknown environment poses a two-pronged prob-lem, where on the one hand we need agents to cover as much of the environment as possible and on the other have a higher density of agents where there are potential targets to maximize detection performance. This paper proposes a fully distributed solution for an ad hoc network of agents to cooperatively search an unknown environment and actively track found targets. The solution combines a distributed pheromone-based coverage control strategy with a distributed target selection mechanism.\",\"PeriodicalId\":431373,\"journal\":{\"name\":\"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IROS47612.2022.9981262\",\"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 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IROS47612.2022.9981262","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

使用多智能体系统在未知环境中主动搜索目标会带来一个双管齐下的问题,一方面我们需要智能体覆盖尽可能多的环境,另一方面在存在潜在目标的地方需要更高密度的智能体以最大化检测性能。本文提出了一种完全分布式的智能体自组网方案,用于协同搜索未知环境并主动跟踪发现的目标。该方案结合了基于分布式信息素的覆盖控制策略和分布式目标选择机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-Time Distributed Multi-Robot Target Tracking via Virtual Pheromones
Actively searching for targets using a multi-agent system in an unknown environment poses a two-pronged prob-lem, where on the one hand we need agents to cover as much of the environment as possible and on the other have a higher density of agents where there are potential targets to maximize detection performance. This paper proposes a fully distributed solution for an ad hoc network of agents to cooperatively search an unknown environment and actively track found targets. The solution combines a distributed pheromone-based coverage control strategy with a distributed target selection mechanism.
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