{"title":"A self-localization and path planning technique for mobile robot navigation","authors":"Jiawei Zhou, H. Lin","doi":"10.1109/WCICA.2011.5970604","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a system to cope with the problem of autonomous mobile robot navigation. It is able to perform path planning and localize the robot in the real world environment. The path planning is first carried out using the known map, and the laser range scanner is then used to localize the robot based on the ICP registration technique. During the robot motion, the potential field is taken into account for obstacle avoidance. For the path planning, the visibility graph is established based on the current position of the robot. The Dijkstra algorithm is then used to find the shortest path to the goal position. Experimental results for both the simulation and real world environment are presented.","PeriodicalId":211049,"journal":{"name":"2011 9th World Congress on Intelligent Control and Automation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 9th World Congress on Intelligent Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCICA.2011.5970604","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
In this paper, we propose a system to cope with the problem of autonomous mobile robot navigation. It is able to perform path planning and localize the robot in the real world environment. The path planning is first carried out using the known map, and the laser range scanner is then used to localize the robot based on the ICP registration technique. During the robot motion, the potential field is taken into account for obstacle avoidance. For the path planning, the visibility graph is established based on the current position of the robot. The Dijkstra algorithm is then used to find the shortest path to the goal position. Experimental results for both the simulation and real world environment are presented.