{"title":"Reliable Navigation Planning Implementation on a Two-Wheeled Mobile Robot","authors":"Élise Crepon, A. Panchea, Alexandre Chapoutot","doi":"10.1109/IRC.2018.00035","DOIUrl":null,"url":null,"abstract":"Autonomous mobile robots must be equipped with appropriate planification and control navigation systems in order to obtain robust behaviours. This study aims at dealing with this kind of problems when implementing on a two wheeled mobile robot. The planning navigation system uses our previously proposed reliable and safe navigation planning algorithm based on the incremental sampling-based planning algorithm, e.g., the widely-used Rapidly-exploring Random Tree (RRT), while the control navigation level consists in a go to goal controller strategy. Through experiments, we demonstrate the usefulness of robust navigation planner in an autonomous navigation schemes, where uncertain localization has to be taken into account.","PeriodicalId":416113,"journal":{"name":"2018 Second IEEE International Conference on Robotic Computing (IRC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Second IEEE International Conference on Robotic Computing (IRC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRC.2018.00035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Autonomous mobile robots must be equipped with appropriate planification and control navigation systems in order to obtain robust behaviours. This study aims at dealing with this kind of problems when implementing on a two wheeled mobile robot. The planning navigation system uses our previously proposed reliable and safe navigation planning algorithm based on the incremental sampling-based planning algorithm, e.g., the widely-used Rapidly-exploring Random Tree (RRT), while the control navigation level consists in a go to goal controller strategy. Through experiments, we demonstrate the usefulness of robust navigation planner in an autonomous navigation schemes, where uncertain localization has to be taken into account.
自主移动机器人必须配备适当的平面化和控制导航系统，才能获得鲁棒性行为。本研究的目的是在两轮移动机器人上实现这类问题。规划导航系统采用我们之前提出的基于增量采样规划算法的可靠安全的导航规划算法，如广泛使用的快速探索随机树(rapid - explore Random Tree, RRT)，而控制导航层则采用go - to - goal控制器策略。通过实验，我们证明了鲁棒导航规划器在自主导航方案中的实用性，其中必须考虑不确定的定位。
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