{"title":"A Formation-Constrained Cooperative Path Planning Method for Multi-autonomous Underwater Vehicles","authors":"Shuangshuang Du, C. Cai, Houjun Wang, Dongwu Li","doi":"10.1109/CIIS.2017.51","DOIUrl":null,"url":null,"abstract":"A novel path planning method based on particle swarm optimization (PSO) is proposed to achieve cooperative formation cruise for multi-autonomous underwater vehicles (AUV). In particular, inspired by the virtual structure approach, particle in PSO is defined as a set of cooperative routes. These routes are composed by a series of navigation points including the initial points and the target points of corresponding vehicles. Given these navigation points, the optimization can be carried out in the search space described by vectors. By designing a reasonable cost function and a particle updating strategy, the method successfully coordinates the time and space of vehicles before vehicles arrived the formation-constrained positions, and simultaneously, preserves the formation constraint and avoids obstacles during the navigation, which provides a new perspective to address the cooperative path planning problem with a formation constraint. The feasibility and effectiveness of the proposed method are validated by experiments.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"300 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Computing Intelligence and Information System (CIIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIIS.2017.51","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 novel path planning method based on particle swarm optimization (PSO) is proposed to achieve cooperative formation cruise for multi-autonomous underwater vehicles (AUV). In particular, inspired by the virtual structure approach, particle in PSO is defined as a set of cooperative routes. These routes are composed by a series of navigation points including the initial points and the target points of corresponding vehicles. Given these navigation points, the optimization can be carried out in the search space described by vectors. By designing a reasonable cost function and a particle updating strategy, the method successfully coordinates the time and space of vehicles before vehicles arrived the formation-constrained positions, and simultaneously, preserves the formation constraint and avoids obstacles during the navigation, which provides a new perspective to address the cooperative path planning problem with a formation constraint. The feasibility and effectiveness of the proposed method are validated by experiments.