{"title":"Incremental Path Planning Using Partial Map Information for Mobile Robots","authors":"X. Lai, S. Ge, P. T. Ong, A. Mamun","doi":"10.1109/ICARCV.2006.345286","DOIUrl":null,"url":null,"abstract":"This paper proposes a practical method for planning paths incrementally for mobile robots in unknown environments using the latest sensory information. A* algorithm was modified in this research for it to be able to handle an occupancy grid map with unknown information. Then the paper presented an algorithm that is able to robustly and incrementally searching for an optimal path based on the partial map simultaneously built by the robot. Waypoints was generated to further optimize the obtained path and were sequentially traced by the robot in a simple, reactive way. Extensive simulations and experiments were carried out to verify the proposed planning algorithm","PeriodicalId":415827,"journal":{"name":"2006 9th International Conference on Control, Automation, Robotics and Vision","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 9th International Conference on Control, Automation, Robotics and Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARCV.2006.345286","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper proposes a practical method for planning paths incrementally for mobile robots in unknown environments using the latest sensory information. A* algorithm was modified in this research for it to be able to handle an occupancy grid map with unknown information. Then the paper presented an algorithm that is able to robustly and incrementally searching for an optimal path based on the partial map simultaneously built by the robot. Waypoints was generated to further optimize the obtained path and were sequentially traced by the robot in a simple, reactive way. Extensive simulations and experiments were carried out to verify the proposed planning algorithm
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