Mobile Robot Monte Carlo Localization in Incomplete Map

摘要：

In order to overcome the difficulty of a mobile robot to perform localization in an incomplete map, an improved particleclustered Monte Carlo Iocalization(MCL) algorithm is proposed.During the process of localization, the robot pose is divided into six kinds of states, and each state corresponds to a particle cluster. Based on computing the transition probability, a MCL algorithm in incomplete environment is realized, which breaks the restriction that the MCL algorithm can only be used in the situation of complete map. Experiment results illustrate the validity of the approach in solving problems of localization in an incomplete map.

关键词： Monte Carlo localization incomplete map state probability transition

作者: Heng Zhang Yan-Li Liu Jin Sun

作者单位: School of Information Engineering East China Jiaotong University Nanchang, China, 330013 School of Software East China Jiaotong University Nanchang, China, 330013

会议类型: 国际会议

会议名称: The 10th International Conference on Intelligent Technologies(第十届智慧科技国际会议 InTech09)

会议地点: 桂林

会议语种:英文

页码: 202-205

在线出版日期: 2009-12-12（万方平台首次上网日期，不代表论文的发表时间）