具有分数阶势场的小型无人机协同寻源系统

Jinlu Han
{"title":"具有分数阶势场的小型无人机协同寻源系统","authors":"Jinlu Han","doi":"10.1109/CCDC.2018.8408307","DOIUrl":null,"url":null,"abstract":"The searching and monitoring of diffusive sources, especially those with dangerous radiative sources, are of great significance to public safety and personal health. Due to the influence of the environment and the field, it is difficult to ensure precise source seeking and real-time performance. Existing searching methods use manned machines, robotics or unmanned ground vehicles (UGVs), which are easily affected by the environmental situation and the field. They are also possible to be blocked during the marching journey, resulting in a failure of the task. The rapid development of small unmanned aircraft system (UAS), which includes unmanned aerial vehicles(UAVs) can solve this problem. In an UAS, UAVs with the installed sensors are able to detect the 3D space in the air, which are barely affected by the ground condition and could communicate with the ground station, and other UAVs via the network. Due to the dangers of the radiative source, it is important to find out the exact location in a short time. Based on the cooperative seeking, an extended Kalman filter (EKF) can be developed to shorten the process of the source seeking, and estimate the radiative source accurately. Considering the actual situation of the UASs-based cooperative source seeking, this paper presents the models of the UAVs and the radiative source, introduces the fractional order potential field (FOPF) for collision avoidance and path planning, establishes the real-world simulation platform, and utilizes the EKF to effectively localize the accurate position of the radiative source.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Small unmanned aircraft systems for cooperative source seeking with fractional order potential fields\",\"authors\":\"Jinlu Han\",\"doi\":\"10.1109/CCDC.2018.8408307\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The searching and monitoring of diffusive sources, especially those with dangerous radiative sources, are of great significance to public safety and personal health. Due to the influence of the environment and the field, it is difficult to ensure precise source seeking and real-time performance. Existing searching methods use manned machines, robotics or unmanned ground vehicles (UGVs), which are easily affected by the environmental situation and the field. They are also possible to be blocked during the marching journey, resulting in a failure of the task. The rapid development of small unmanned aircraft system (UAS), which includes unmanned aerial vehicles(UAVs) can solve this problem. In an UAS, UAVs with the installed sensors are able to detect the 3D space in the air, which are barely affected by the ground condition and could communicate with the ground station, and other UAVs via the network. Due to the dangers of the radiative source, it is important to find out the exact location in a short time. Based on the cooperative seeking, an extended Kalman filter (EKF) can be developed to shorten the process of the source seeking, and estimate the radiative source accurately. Considering the actual situation of the UASs-based cooperative source seeking, this paper presents the models of the UAVs and the radiative source, introduces the fractional order potential field (FOPF) for collision avoidance and path planning, establishes the real-world simulation platform, and utilizes the EKF to effectively localize the accurate position of the radiative source.\",\"PeriodicalId\":409960,\"journal\":{\"name\":\"2018 Chinese Control And Decision Conference (CCDC)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Chinese Control And Decision Conference (CCDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCDC.2018.8408307\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Chinese Control And Decision Conference (CCDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2018.8408307","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

寻找和监测扩散源,特别是具有危险辐射源的扩散源,对公共安全和个人健康具有重要意义。由于环境和现场的影响,难以保证精确的寻源和实时性。现有的搜索方法使用载人机器、机器人或无人地面车辆(ugv),这些方法容易受到环境状况和现场的影响。他们也有可能在行进过程中被阻挡,导致任务失败。包括无人机在内的小型无人机系统(UAS)的迅速发展可以解决这一问题。在无人机系统中,安装了传感器的无人机能够探测空中的3D空间,几乎不受地面条件的影响,并且可以通过网络与地面站和其他无人机进行通信。由于辐射源的危险性,在短时间内查明其确切位置是很重要的。在协同搜索的基础上,提出了一种扩展卡尔曼滤波(EKF)来缩短寻源过程,准确估计辐射源。针对无人机协同寻源的实际情况,建立了无人机与辐射源的模型,引入了用于避碰和路径规划的分数阶势场(FOPF),建立了实景仿真平台,利用分数阶势场有效定位辐射源的精确位置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Small unmanned aircraft systems for cooperative source seeking with fractional order potential fields
The searching and monitoring of diffusive sources, especially those with dangerous radiative sources, are of great significance to public safety and personal health. Due to the influence of the environment and the field, it is difficult to ensure precise source seeking and real-time performance. Existing searching methods use manned machines, robotics or unmanned ground vehicles (UGVs), which are easily affected by the environmental situation and the field. They are also possible to be blocked during the marching journey, resulting in a failure of the task. The rapid development of small unmanned aircraft system (UAS), which includes unmanned aerial vehicles(UAVs) can solve this problem. In an UAS, UAVs with the installed sensors are able to detect the 3D space in the air, which are barely affected by the ground condition and could communicate with the ground station, and other UAVs via the network. Due to the dangers of the radiative source, it is important to find out the exact location in a short time. Based on the cooperative seeking, an extended Kalman filter (EKF) can be developed to shorten the process of the source seeking, and estimate the radiative source accurately. Considering the actual situation of the UASs-based cooperative source seeking, this paper presents the models of the UAVs and the radiative source, introduces the fractional order potential field (FOPF) for collision avoidance and path planning, establishes the real-world simulation platform, and utilizes the EKF to effectively localize the accurate position of the radiative source.
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
期刊最新文献
An improved K-means algorithm for reciprocating compressor fault diagnosis Bond graph modeling and fault injection of CRH5 traction system Design of human eye information detection system Multi-leak diagnosis and isolation in oil pipelines based on Unscented Kalman filter Local logic optimization algorithm for autonomous mobile robot based on fuzzy logic
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1