{"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}
引用次数: 3
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.