An SLAM algorithm based on improved UKF
Because of using system nonlinear model directly UKF overcomes the shortcomings of the methods such as EKF that they easily introduces truncation errors in the process of lining model .So it is widely used in SLAM problem. Because the square root of filter has the advantages that it can ensure the covariance matrix nonnegative, a square root version of the UKF was included in the SLAM problem that improve the performance of UKF-SLAM algorithm. Simulation result shows that this algorithm is effective.
Mobile Robot SLAM Unscented Kalman filter
Liping Qu Shuiqing He Yongyin Qu
Department of Electric Information Engineering College University of Beihua, Jilin 132021, China
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
4171-4174
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）