计算机工程2012，Vol.38Issue(21)：1-4,4.DOI:10.3969/j.issn.1000-3428.2012.21.001
一种新的抗外部干扰EKF-SLAM算法
A Novel EKF-SLAM Algorithm Against Outlier Disturbance
吕太之1
作者信息
- 1. 南京理工大学计算机科学与技术学院,南京210094
- 折叠
摘要
Abstract
There is not only sensor noise, but also outlier disturbance when a robot explores in unknown environments. The traditional EKF-SLAM algorithm does not consider the impact of outlier disturbance that may lead to positioning failure. The new algorithm detects the outlier disturbance by comparing two observations result using polar coordinates. Covariance would be inflated when disturbance is detected, so that system state of uncertainty is expanded and the state quickly converges to the true value. Simulation results show that the proposed algorithm is better than EKF-SLAM both in mobile robot SLAM accuracy and robustness.关键词
同时定位与地图创建/扩展卡尔曼滤波/外部干扰/方差膨胀/一致性/移动机器人Key words
Simultaneous Localization and Mapping(SLAM)/ Extended Kalman Filter(EKF)/ outlier disturbance/ covariance inflation/ consistency/ mobile robot分类
信息技术与安全科学引用本文复制引用
吕太之..一种新的抗外部干扰EKF-SLAM算法[J].计算机工程,2012,38(21):1-4,4.
