{"title":"Path planing and tracking for multi-robot system based on improved PSO algorithm","authors":"Mao Yang, Chun-zhe Li","doi":"10.1109/MEC.2011.6025799","DOIUrl":null,"url":null,"abstract":"A new algorithm based on improved particle swarm optimization (PSO) of cubic splines is proposed for multiple mobile robot path planning. The center path is described by string of cubic splines, thus the path planning is equivalent to parameter optimization of particular cubic splines. Improved PSO is introduced to get the optimal path for its fast convergence and global search character. PD controller is adopted to tracking the center optimal path. Experimental results show that a collision-avoidance path can be found effectively among obstacles and each other by the proposed algorithm.","PeriodicalId":386083,"journal":{"name":"2011 International Conference on Mechatronic Science, Electric Engineering and Computer (MEC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Mechatronic Science, Electric Engineering and Computer (MEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MEC.2011.6025799","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
A new algorithm based on improved particle swarm optimization (PSO) of cubic splines is proposed for multiple mobile robot path planning. The center path is described by string of cubic splines, thus the path planning is equivalent to parameter optimization of particular cubic splines. Improved PSO is introduced to get the optimal path for its fast convergence and global search character. PD controller is adopted to tracking the center optimal path. Experimental results show that a collision-avoidance path can be found effectively among obstacles and each other by the proposed algorithm.