M. Ono, Greg N. Droge, H. F. Grip, O. Toupet, C. Scrapper, A. Rahmani
{"title":"Road-following formation control of autonomous ground vehicles","authors":"M. Ono, Greg N. Droge, H. F. Grip, O. Toupet, C. Scrapper, A. Rahmani","doi":"10.1109/CDC.2015.7402954","DOIUrl":null,"url":null,"abstract":"This work presents a novel cooperative path planning for formation keeping robots traversing along a road with obstacles and possible narrow passages. A unique challenge in this problem is a requirement for spatial and temporal coordination between vehicles while ensuring collision and obstacle avoidance. A two-step approach is used for fast real-time planning. The first step uses the A* search on a spatiotemporally extended graph to generate an obstacle-free path for the agent while the second step refines this path through local optimization to comply with dynamic and other vehicle constraints. This approach keeps robots close to their intended formation while giving them flexibility to negotiate narrow passages and obstacles, adhering to any given constraints.","PeriodicalId":308101,"journal":{"name":"2015 54th IEEE Conference on Decision and Control (CDC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 54th IEEE Conference on Decision and Control (CDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.2015.7402954","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 work presents a novel cooperative path planning for formation keeping robots traversing along a road with obstacles and possible narrow passages. A unique challenge in this problem is a requirement for spatial and temporal coordination between vehicles while ensuring collision and obstacle avoidance. A two-step approach is used for fast real-time planning. The first step uses the A* search on a spatiotemporally extended graph to generate an obstacle-free path for the agent while the second step refines this path through local optimization to comply with dynamic and other vehicle constraints. This approach keeps robots close to their intended formation while giving them flexibility to negotiate narrow passages and obstacles, adhering to any given constraints.