Cooperative exploration strategy for micro-aerial vehicles fleet

Nesrine Mahdoui, V. Fremont, E. Natalizio
{"title":"Cooperative exploration strategy for micro-aerial vehicles fleet","authors":"Nesrine Mahdoui, V. Fremont, E. Natalizio","doi":"10.1109/MFI.2017.8170426","DOIUrl":null,"url":null,"abstract":"In this paper, the problem of the exploration of an unknown environment by deploying a fleet of Micro-Aerial Vehicles (MAV) is considered. As a single robot has already proven its efficiency for this task, the challenge is to extend it to a multi-robots system to reduce the exploration time. For this purpose, a cooperative navigation strategy is proposed based on a specific utility function and inter-robots data exchange. The novelty comes from the exchange of the frontiers points instead of maps, which allows to reduce computation and data amount within the network. The proposed system has been implemented and tested under ROS using the Gazebo simulator. The results demonstrate that the proposed navigation strategy efficiently spreads robots over the environment for a faster exploration.","PeriodicalId":402371,"journal":{"name":"2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MFI.2017.8170426","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

In this paper, the problem of the exploration of an unknown environment by deploying a fleet of Micro-Aerial Vehicles (MAV) is considered. As a single robot has already proven its efficiency for this task, the challenge is to extend it to a multi-robots system to reduce the exploration time. For this purpose, a cooperative navigation strategy is proposed based on a specific utility function and inter-robots data exchange. The novelty comes from the exchange of the frontiers points instead of maps, which allows to reduce computation and data amount within the network. The proposed system has been implemented and tested under ROS using the Gazebo simulator. The results demonstrate that the proposed navigation strategy efficiently spreads robots over the environment for a faster exploration.
微型飞行器编队协同探索策略
本文研究了部署微型飞行器(MAV)对未知环境进行探测的问题。由于单机器人已经证明了它在这项任务中的效率,挑战是将其扩展到多机器人系统以减少探索时间。为此,提出了一种基于特定效用函数和机器人间数据交换的协同导航策略。新颖之处在于交换边界点而不是地图,这可以减少网络内的计算和数据量。建议的系统已在ROS下使用Gazebo模拟器进行了实施和测试。结果表明,所提出的导航策略可以有效地将机器人扩展到环境中,从而实现更快的探索。
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