R. Rashid, N. Perumal, I. Elamvazuthi, M. Tageldeen, M.K.A.Ahmed Khan, S. Parasuraman
{"title":"基于蚁群算法的移动机器人路径规划","authors":"R. Rashid, N. Perumal, I. Elamvazuthi, M. Tageldeen, M.K.A.Ahmed Khan, S. Parasuraman","doi":"10.1109/ROMA.2016.7847836","DOIUrl":null,"url":null,"abstract":"Ant colony optimization (ACO) technique is proposed to solve the mobile robot path planning (MRPP) problem. In order to demonstrate the effectiveness of ACO in solving the MRPP problem, several maps of varying complexity used by an earlier researcher is used for evaluation. Each map consists of static obstacles in different arrangements. Besides that, each map has a grid representation with an equal number of rows and columns. The performance of the proposed ACO is tested on a given set of maps. Overall, the results demonstrate the effectiveness of the proposed approach for path planning.","PeriodicalId":409977,"journal":{"name":"2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation (ROMA)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"93","resultStr":"{\"title\":\"Mobile robot path planning using Ant Colony Optimization\",\"authors\":\"R. Rashid, N. Perumal, I. Elamvazuthi, M. Tageldeen, M.K.A.Ahmed Khan, S. Parasuraman\",\"doi\":\"10.1109/ROMA.2016.7847836\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ant colony optimization (ACO) technique is proposed to solve the mobile robot path planning (MRPP) problem. In order to demonstrate the effectiveness of ACO in solving the MRPP problem, several maps of varying complexity used by an earlier researcher is used for evaluation. Each map consists of static obstacles in different arrangements. Besides that, each map has a grid representation with an equal number of rows and columns. The performance of the proposed ACO is tested on a given set of maps. Overall, the results demonstrate the effectiveness of the proposed approach for path planning.\",\"PeriodicalId\":409977,\"journal\":{\"name\":\"2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation (ROMA)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"93\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation (ROMA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ROMA.2016.7847836\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation (ROMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROMA.2016.7847836","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mobile robot path planning using Ant Colony Optimization
Ant colony optimization (ACO) technique is proposed to solve the mobile robot path planning (MRPP) problem. In order to demonstrate the effectiveness of ACO in solving the MRPP problem, several maps of varying complexity used by an earlier researcher is used for evaluation. Each map consists of static obstacles in different arrangements. Besides that, each map has a grid representation with an equal number of rows and columns. The performance of the proposed ACO is tested on a given set of maps. Overall, the results demonstrate the effectiveness of the proposed approach for path planning.
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