机器人2013，Vol.35Issue(2)：186-193,8.DOI:10.3724/SP.J.1218.2013.00186
平方根容积卡尔曼滤波在移动机器人SLAM中的应用
Square-Root Cubature Kalman Filter and Its Application to SLAM of an Mobile Robot
摘要
Abstract
For simultaneous localization and mapping (SLAM) of robots, a new solution is proposed, named square-root cubature Kalman filter based SLAM algorithm (SCKF-SLAM). The main contribution of the proposed algorithm is that the SLAM posterior probability density is calculated by using the square root cubature Kalman filter in order to reduce linearization error and improve SLAM accuracy. Instead of covariance matrixes, square-root factors are used in the proposed SLAM algorithm to avoid the time-consuming Cholesky decompositions and improve the calculation efficiency. In experiments, the proposed algorithm is compared with extended Kalman filter SLAM (EKF-SLAM) and unscented Kalman filter SLAM (UKF-SLAM). The results show that compared with EKF-SLAM, precision of SCKF-SLAM is doubled, and compared with UKF-SLAM, SCKF-SLAM saves a quarter of computation resources.关键词
移动机器人/卡尔曼滤波/线性化/容积变换Key words
mobile robot/ Kalman filter/ linearization/ cubature transformation分类
信息技术与安全科学引用本文复制引用
康轶非,宋永端,宋宇,闫德立,李丹勇..平方根容积卡尔曼滤波在移动机器人SLAM中的应用[J].机器人,2013,35(2):186-193,8.基金项目
国家自然科学基金资助项目(61134001,60909055) （61134001,60909055）
国家973计划资助项目(2012CB215202) （2012CB215202）
国家863计划资助项目(SS2012AA052302) （SS2012AA052302）
中央高校基本科研业务费专项资金资助项目(2012JBM017,2011YJS287). （2012JBM017,2011YJS287）
