{"title":"Toward informative planning for cooperative underwater localization","authors":"Jeffrey M. Walls, R. Eustice","doi":"10.1109/OCEANS.2014.7003099","DOIUrl":null,"url":null,"abstract":"This paper reports on an algorithm for planning a practical trajectory for a surface vehicle that provides range measurements to an autonomous underwater vehicle (AUV). We consider server-client cooperative localization in which a server vehicle provides relative range constraints to minimize the uncertainty of a client vehicle. Our approach assumes the nominal client mission plan is available and draws potential server trajectories from a set of parameterized trajectory classes. We provide a comparative evaluation over several simulations, for both a single client and multiple clients, demonstrating that our algorithm computes operationally practical server paths and performs well relative to existing planning frameworks.","PeriodicalId":368693,"journal":{"name":"2014 Oceans - St. John's","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Oceans - St. John's","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OCEANS.2014.7003099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
This paper reports on an algorithm for planning a practical trajectory for a surface vehicle that provides range measurements to an autonomous underwater vehicle (AUV). We consider server-client cooperative localization in which a server vehicle provides relative range constraints to minimize the uncertainty of a client vehicle. Our approach assumes the nominal client mission plan is available and draws potential server trajectories from a set of parameterized trajectory classes. We provide a comparative evaluation over several simulations, for both a single client and multiple clients, demonstrating that our algorithm computes operationally practical server paths and performs well relative to existing planning frameworks.