{"title":"Multi-robots coverage approach","authors":"R. Chellali, K. Baizid","doi":"10.1109/RIISS.2014.7009171","DOIUrl":null,"url":null,"abstract":"In this paper we present a full and effective system allowing the deployment of N semi-autonomous robots in order to cover a given area for video surveillance and search purposes. The coverage problem is solved through a new technique based on the exploitation of Voronoi tessellations. To supervise a given area, a set of viewpoints are extracted, then visited by a group of mobile rover. Robots paths are calculated by resorting a salesman problem through Multi-objective Genetic Algorithms. In the running phase, robots deal with both motion and sensors uncertainties while performing the pre-established paths. Results of indoor scenario are given.","PeriodicalId":270157,"journal":{"name":"2014 IEEE Symposium on Robotic Intelligence in Informationally Structured Space (RiiSS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Symposium on Robotic Intelligence in Informationally Structured Space (RiiSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RIISS.2014.7009171","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
In this paper we present a full and effective system allowing the deployment of N semi-autonomous robots in order to cover a given area for video surveillance and search purposes. The coverage problem is solved through a new technique based on the exploitation of Voronoi tessellations. To supervise a given area, a set of viewpoints are extracted, then visited by a group of mobile rover. Robots paths are calculated by resorting a salesman problem through Multi-objective Genetic Algorithms. In the running phase, robots deal with both motion and sensors uncertainties while performing the pre-established paths. Results of indoor scenario are given.