{"title":"Experimental Validation of a Multirobot Distributed Receding Horizon Motion Planning Approach","authors":"J. M. Filho, E. Lucet, David Filliat","doi":"10.1109/ICARCV.2018.8581365","DOIUrl":null,"url":null,"abstract":"This paper addresses the problem of motion planning for a multirobot system in a partially known environment where conditions such as uncertainty about robots' positions and communication delays are real. In particular, we detail the use of a Distributed Receding Horizon Approach that guarantees collision avoidance with static obstacles and between robots communicating with each other. Underlying optimization problems are solved by using a Sequential Least Squares Programming algorithm. Experiments with real nonholonomic mobile platforms are performed. The proposed framework is compared with the Dynamic Window approach to motion planning in a single robot setup. A second experiment shows results for a multirobot case using two robots where collision is avoided even in presence of significant localization uncertainties.","PeriodicalId":395380,"journal":{"name":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARCV.2018.8581365","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
This paper addresses the problem of motion planning for a multirobot system in a partially known environment where conditions such as uncertainty about robots' positions and communication delays are real. In particular, we detail the use of a Distributed Receding Horizon Approach that guarantees collision avoidance with static obstacles and between robots communicating with each other. Underlying optimization problems are solved by using a Sequential Least Squares Programming algorithm. Experiments with real nonholonomic mobile platforms are performed. The proposed framework is compared with the Dynamic Window approach to motion planning in a single robot setup. A second experiment shows results for a multirobot case using two robots where collision is avoided even in presence of significant localization uncertainties.