{"title":"Collision-Free Navigation for Multiple Robots in Dynamic Environment","authors":"Y. Yeh, Wei-Cheng Wang, Rongping Chen","doi":"10.1109/MESA55290.2022.10004454","DOIUrl":null,"url":null,"abstract":"To aim at the collision-free navigation framework for multi-robot systems in dynamic environment, this work develops a two-layer methodology to implement the obstacle avoidance for multiple robots. A global planner is introduced to construct the global plan at the high layer. Combining the artificial potential field with the pure-pursuit algorithm, a low-layer local planner is designed to generate the control commands for tracking the waypoints obtained from the global plan. Moreover, the rolling windows method, the obstacle filter, and the multi-robot coordination strategy are also introduced to enhance the robustness of the proposed approach implemented on practical robots. Both simulations and experimental results are presented to verify the feasibility of the proposed method.","PeriodicalId":410029,"journal":{"name":"2022 18th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)","volume":"47 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 18th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MESA55290.2022.10004454","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
To aim at the collision-free navigation framework for multi-robot systems in dynamic environment, this work develops a two-layer methodology to implement the obstacle avoidance for multiple robots. A global planner is introduced to construct the global plan at the high layer. Combining the artificial potential field with the pure-pursuit algorithm, a low-layer local planner is designed to generate the control commands for tracking the waypoints obtained from the global plan. Moreover, the rolling windows method, the obstacle filter, and the multi-robot coordination strategy are also introduced to enhance the robustness of the proposed approach implemented on practical robots. Both simulations and experimental results are presented to verify the feasibility of the proposed method.