An Adaptive Square Root Cubature Kalman Filter based SLAM Algorithm for Mobile Robots

被引：0
|
作者：
Cai, Jun [1 ]
Zhong, Xiaolin [1 ]
机构：
[1] Chongqing Univ Posts & Telecommun, Sch Automat, Chongqing, Peoples R China
来源：
2015 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION | 2015年
关键词：
SLAM algorithm; ASRCKF; Sage-Husa estimator; Adaptive; Mobile robot;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
For simultaneous localization and mapping (SLAM) of mobile robots, an innovative solution is proposed, named adaptive square root cubature Kalman filter based SLAM algorithm (ASRCKF-SLAM). The main contribution of the proposed algorithm lies that: 1) Square root factors are used in the proposed ASRCKF-SLAM algorithm to improve the calculation efficiency by avoiding the time-consuming Cholesky decompositions. 2) Using the adaptive Sage-Husa estimator to solve the large estimation errors or even divergence problem caused by the time-varying or unknown noise. Simulation results obtained demonstrate that the proposed ASRCKF-SLAM algorithm is superior to the existed SLAM method in the aspect of estimation accuracy and computational efficiency.
引用
收藏
页码：2215 / 2219
页数：5
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