{"title":"基于遗传算法的多机器人路径规划与路径协调:扩展摘要","authors":"Muthumeena Muthiah, A. Saad","doi":"10.1145/3077286.3077327","DOIUrl":null,"url":null,"abstract":"Planning optimal paths for multiple robots is computationally expensive. In this research, we provide a Genetic Algorithm implementation for multi robot path planning. Path planning for multiple mobile robots must devise a collision-free path for each robot. The paper presents a Genetic Algorithm multi robot path planner that we developed to provide a solution to the problem. Experimental results using m3pi robots confirm the usefulness of the proposed solution in a variety of scenarios such as multi robot navigation as well as scenarios that require coordination of multiple robots to achieve a common goal such as pushing a box or trapping a prey.","PeriodicalId":91384,"journal":{"name":"Proceedings of the 2014 ACM Southeast Regional Conference","volume":"39 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2017-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Multi Robot Path Planning and Path Coordination Using Genetic Algorithms: Extended Abstract\",\"authors\":\"Muthumeena Muthiah, A. Saad\",\"doi\":\"10.1145/3077286.3077327\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Planning optimal paths for multiple robots is computationally expensive. In this research, we provide a Genetic Algorithm implementation for multi robot path planning. Path planning for multiple mobile robots must devise a collision-free path for each robot. The paper presents a Genetic Algorithm multi robot path planner that we developed to provide a solution to the problem. Experimental results using m3pi robots confirm the usefulness of the proposed solution in a variety of scenarios such as multi robot navigation as well as scenarios that require coordination of multiple robots to achieve a common goal such as pushing a box or trapping a prey.\",\"PeriodicalId\":91384,\"journal\":{\"name\":\"Proceedings of the 2014 ACM Southeast Regional Conference\",\"volume\":\"39 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2014 ACM Southeast Regional Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3077286.3077327\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2014 ACM Southeast Regional Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3077286.3077327","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi Robot Path Planning and Path Coordination Using Genetic Algorithms: Extended Abstract
Planning optimal paths for multiple robots is computationally expensive. In this research, we provide a Genetic Algorithm implementation for multi robot path planning. Path planning for multiple mobile robots must devise a collision-free path for each robot. The paper presents a Genetic Algorithm multi robot path planner that we developed to provide a solution to the problem. Experimental results using m3pi robots confirm the usefulness of the proposed solution in a variety of scenarios such as multi robot navigation as well as scenarios that require coordination of multiple robots to achieve a common goal such as pushing a box or trapping a prey.