Shaojing Wang, Tao He, Hui Sheng, Peng Xu, Yiping Ji
{"title":"Game Theory based Inspection Robots Path Planning in Substations","authors":"Shaojing Wang, Tao He, Hui Sheng, Peng Xu, Yiping Ji","doi":"10.1109/ACPEE53904.2022.9783782","DOIUrl":null,"url":null,"abstract":"Inspection robots are more and more popular in substations. However, due to the complex scene and large number of temperature measurement points, inspection robots path generation is still a challenge. In this paper, a game-theory-based method is proposed to solve this problem. We first model the substation, robots and environment factors in an effective and reasonable way. Then the algorithm including rough selection and game-theory-based refinement steps is utilized to generate the best set of parking points. Experiments under different conditions show that our method is much better than manual work and related model in the aspects of shooting distance, angle, number of parking points and inspection completion rate.","PeriodicalId":118112,"journal":{"name":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPEE53904.2022.9783782","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Inspection robots are more and more popular in substations. However, due to the complex scene and large number of temperature measurement points, inspection robots path generation is still a challenge. In this paper, a game-theory-based method is proposed to solve this problem. We first model the substation, robots and environment factors in an effective and reasonable way. Then the algorithm including rough selection and game-theory-based refinement steps is utilized to generate the best set of parking points. Experiments under different conditions show that our method is much better than manual work and related model in the aspects of shooting distance, angle, number of parking points and inspection completion rate.