Zheping Yan, Jiyun Li, J. Zou, Juan Li, Rong Zhong
{"title":"A hybrid PSO-WG algorithm for AUV path planning in unknown oceanic environment","authors":"Zheping Yan, Jiyun Li, J. Zou, Juan Li, Rong Zhong","doi":"10.1109/USYS.2018.8779121","DOIUrl":null,"url":null,"abstract":"A new path planning algorithm is presented for autonomous underwater vehicle (AUV) in undiscovered ocean environments based on combining particle swarm optimization (PSO) with waypoint guidance (WG). In this algorithm, multi-beams forward looking sonar (FLS) is utilized to discover obstacles, and PSO algorithm is adopted to generate appropriate waypoints, an optimal path with low power consumption and free of collision is generated by following these waypoints. Finally, the simulation experiment is conducted in MATLAB 2015, the simulation results show that this algorithm can generate optimal paths with shorter path length and better smoothness.","PeriodicalId":299885,"journal":{"name":"2018 IEEE 8th International Conference on Underwater System Technology: Theory and Applications (USYS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 8th International Conference on Underwater System Technology: Theory and Applications (USYS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/USYS.2018.8779121","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A new path planning algorithm is presented for autonomous underwater vehicle (AUV) in undiscovered ocean environments based on combining particle swarm optimization (PSO) with waypoint guidance (WG). In this algorithm, multi-beams forward looking sonar (FLS) is utilized to discover obstacles, and PSO algorithm is adopted to generate appropriate waypoints, an optimal path with low power consumption and free of collision is generated by following these waypoints. Finally, the simulation experiment is conducted in MATLAB 2015, the simulation results show that this algorithm can generate optimal paths with shorter path length and better smoothness.