{"title":"基于MOPSO算法的高效分层机器人路径规划方法","authors":"Han Wu, Huiliang Shang","doi":"10.1109/WRC-SARA.2018.8584231","DOIUrl":null,"url":null,"abstract":"A layered path planning approach is designed to find a collision free and global optimal path from the start position to goal position in static environment. In the first two levels, called preprocessing, Delaunay triangulation and Dijkstra’s algorithm are applied to generate the initial approximate optimal paths. Then considering two objectives, minimizing the path length and maximizing the path smoothness, the improved multi-objective particle swarm optimization is used to optimize the initial paths in the third level. Various experimental results in different environments show that the proposed layered planning method can avoid the local optimal path and accelerate the convergence.","PeriodicalId":185881,"journal":{"name":"2018 WRC Symposium on Advanced Robotics and Automation (WRC SARA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An efficient layered robot path planning approach based on MOPSO algorithm\",\"authors\":\"Han Wu, Huiliang Shang\",\"doi\":\"10.1109/WRC-SARA.2018.8584231\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A layered path planning approach is designed to find a collision free and global optimal path from the start position to goal position in static environment. In the first two levels, called preprocessing, Delaunay triangulation and Dijkstra’s algorithm are applied to generate the initial approximate optimal paths. Then considering two objectives, minimizing the path length and maximizing the path smoothness, the improved multi-objective particle swarm optimization is used to optimize the initial paths in the third level. Various experimental results in different environments show that the proposed layered planning method can avoid the local optimal path and accelerate the convergence.\",\"PeriodicalId\":185881,\"journal\":{\"name\":\"2018 WRC Symposium on Advanced Robotics and Automation (WRC SARA)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 WRC Symposium on Advanced Robotics and Automation (WRC SARA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WRC-SARA.2018.8584231\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 WRC Symposium on Advanced Robotics and Automation (WRC SARA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WRC-SARA.2018.8584231","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An efficient layered robot path planning approach based on MOPSO algorithm
A layered path planning approach is designed to find a collision free and global optimal path from the start position to goal position in static environment. In the first two levels, called preprocessing, Delaunay triangulation and Dijkstra’s algorithm are applied to generate the initial approximate optimal paths. Then considering two objectives, minimizing the path length and maximizing the path smoothness, the improved multi-objective particle swarm optimization is used to optimize the initial paths in the third level. Various experimental results in different environments show that the proposed layered planning method can avoid the local optimal path and accelerate the convergence.