{"title":"基于遗传算法的群体机器人运动规划","authors":"Chien-Chou Lin, Po-Yuan Hsiao, Kun-Cheng Chen","doi":"10.1109/BWCCA.2010.128","DOIUrl":null,"url":null,"abstract":"In this paper, a potential-based genetic algorithm is proposed for formation control of robot swarm. The proposed algorithm consists of a global path planner and a motion planner. The global path planning algorithm searches a path, which the center of robot swarm should follow, within a Voronoi diagram of the free space. The motion planning is a genetic algorithm based on artificial potential models. The potential functions are used as a repulsion to keep robots away from obstacles and as an attraction/repulsion to keep robot swarm within a certain distance. With Voronoi diagram and potential models, the algorithm plans safe paths efficiently and the formation of robot swarm is also maintained.","PeriodicalId":196401,"journal":{"name":"2010 International Conference on Broadband, Wireless Computing, Communication and Applications","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"A Motion Planning of Swarm Robots Using Genetic Algorithm\",\"authors\":\"Chien-Chou Lin, Po-Yuan Hsiao, Kun-Cheng Chen\",\"doi\":\"10.1109/BWCCA.2010.128\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a potential-based genetic algorithm is proposed for formation control of robot swarm. The proposed algorithm consists of a global path planner and a motion planner. The global path planning algorithm searches a path, which the center of robot swarm should follow, within a Voronoi diagram of the free space. The motion planning is a genetic algorithm based on artificial potential models. The potential functions are used as a repulsion to keep robots away from obstacles and as an attraction/repulsion to keep robot swarm within a certain distance. With Voronoi diagram and potential models, the algorithm plans safe paths efficiently and the formation of robot swarm is also maintained.\",\"PeriodicalId\":196401,\"journal\":{\"name\":\"2010 International Conference on Broadband, Wireless Computing, Communication and Applications\",\"volume\":\"94 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Broadband, Wireless Computing, Communication and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BWCCA.2010.128\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Broadband, Wireless Computing, Communication and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BWCCA.2010.128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Motion Planning of Swarm Robots Using Genetic Algorithm
In this paper, a potential-based genetic algorithm is proposed for formation control of robot swarm. The proposed algorithm consists of a global path planner and a motion planner. The global path planning algorithm searches a path, which the center of robot swarm should follow, within a Voronoi diagram of the free space. The motion planning is a genetic algorithm based on artificial potential models. The potential functions are used as a repulsion to keep robots away from obstacles and as an attraction/repulsion to keep robot swarm within a certain distance. With Voronoi diagram and potential models, the algorithm plans safe paths efficiently and the formation of robot swarm is also maintained.