Convergence analysis for extended Kalman filter based SLAM
Convergence analysis for extended Kalman filter based SLAM
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DOI：
10.1109/robot.2006.1641746
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发表时间：
2006-05
期刊：
影响因子：
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通讯作者：
Shoudong Huang;G. Dissanayake
中科院分区：
文献类型：
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作者：
Shoudong Huang;G. Dissanayake
本文的主要贡献是扩展卡尔曼滤波（EKF）的解决方案的同时定位和地图（SLAM）问题的理论分析。给出了一般非线性二维SLAM的收敛性质。证据清楚地表明，机器人的方向误差有显着的影响的限制和/或下限的地标位置估计的不确定性。最后，对EKF SLAM的性能进行了分析，并对最近发现的EKF SLAM中的不一致性进行了理论分析
The main contribution of this paper is a theoretical analysis of the extended Kalman filter (EKF) based solution to the simultaneous localisation and mapping (SLAM) problem. The convergence properties for the general nonlinear two-dimensional SLAM are provided. The proofs clearly show that the robot orientation error has a significant effect on the limit and/or the lower bound of the uncertainty of the landmark location estimates. Furthermore, some insights to the performance of EKF SLAM and a theoretical analysis on the inconsistencies in EKF SLAM that have been recently observed are given