Square-Root Unscented Kalman Filter Based Simultaneous Localization and Mapping

摘要：

Simultaneous localization and mapping (SLAM) is concerned to be the key point to realize the real autonomy of mobile robot. Unscented Kalman filter (UKF) is widely applied in SLAM problem because of its directly using of nonlinear model. Concerning that square root filter can ensure non-negative definite of the covariance matrix, this article introduced a square-root unscented Kalman filter into SLAM problem and ensured its stability. This algorithm also gained a more accurate estimation compared to UKF based SLAM. Simulation results showed that this algorithm is effective.

关键词： Simultaneous localization and mapping Unscented Kalman filter Mobile robot

作者: Shurong Li Pengfei Ni

作者单位: College of Information and Control Engineering China University of Petroleum Dongying,Shandong 257061,China

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-5

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）