A COMPARISON OF INFORMATION FUSION METHODS FOR LOCATING INTELLIGENT MOBILE ROBOT

摘要：

Self-localization methods for intelligent mobile robot can be found from literatures. Here, we studied two information fusion methods, namely Extended Kalman Filter and Unscented Kalman Filter. They are used to locate the pose of mobile robot that is navigating in the indoor environment. To analyze the performance of the two filters, they were used respectively to fuse the information coming from the onboard odometry and unidirectional camera. We built the nonlinear models for these two sensors and studied the propagation of uncertainty transformed by the given nonlinear system.Finally we drew a comparison between the two approaches based on the SmartROB2 mobile robot and the performance analyses are given accordingly.

关键词： Self-localization Extended Kalman Filter Unscented Kaiman Filter Intelligent mobile robot Information fusion

作者: KE WANG YAN ZHUANG WEI WANG

作者单位: Research Center of Information and Control, Dalian University of Technology, Dalian 116024, China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 1762-1767

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）