{"title":"The path planning of cleaner robot for coverage region using Genetic Algorithms","authors":"Mohamed Amine Yakoubi, Mohamed Tayeb Laskri","doi":"10.1016/j.jides.2016.05.004","DOIUrl":null,"url":null,"abstract":"<div><p>The vacuum cleaner robot should have a mechanism such as the artificial intelligence to solve the problem of cleaning the entire environment areas taking into account some factors such as the number of turns and the length of the trajectory. This robot’s mechanism or task is known as the path planning of coverage region (PPCR). In this paper, to resolve the problem of PPCR in a room environment, we propose an evolutionary approach. The latter is based on Genetic Algorithms (GA) which, consist of several steps to get the solutions. Each gene represents the robot position and some of chromosomes represent also the mini-path. In addition, this algorithm helps the robot to pass through every part of the environment by avoiding obstacles using different sensors. The results of simulation and comparison studies demonstrate the effectiveness and efficiency of the proposed approach.</p></div>","PeriodicalId":100792,"journal":{"name":"Journal of Innovation in Digital Ecosystems","volume":"3 1","pages":"Pages 37-43"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jides.2016.05.004","citationCount":"75","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Innovation in Digital Ecosystems","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352664516300050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 75
Abstract
The vacuum cleaner robot should have a mechanism such as the artificial intelligence to solve the problem of cleaning the entire environment areas taking into account some factors such as the number of turns and the length of the trajectory. This robot’s mechanism or task is known as the path planning of coverage region (PPCR). In this paper, to resolve the problem of PPCR in a room environment, we propose an evolutionary approach. The latter is based on Genetic Algorithms (GA) which, consist of several steps to get the solutions. Each gene represents the robot position and some of chromosomes represent also the mini-path. In addition, this algorithm helps the robot to pass through every part of the environment by avoiding obstacles using different sensors. The results of simulation and comparison studies demonstrate the effectiveness and efficiency of the proposed approach.