摘要
针对传统的基于扩展卡尔曼滤波的SLAM算法对环境干扰修复速度较慢的缺陷,提出一种EKF-SLAM的改进方法。通过比较EKF-SLAM算法的预测和观测两个过程所得数据,判断是否存在较大的环境干扰。若环境干扰较大,则加大先验估计误差协方差的调整,使状态在经过校正后更快速地接近真实值,提高算法的实时性和抗干扰性。最后使用Matlab对改进EKF-SLAM进行仿真实验,结果表明改进EKF-SLAM算法的有效性和估计精度都比传统EKF-SLAM高。
The traditional SLAM algorithm based on extended kalmanfilter has a problem with low speed of repairing environmentaldisturbance. To solve the problem, this paper proposes an improved method of EKF-SLAM. The simulation of the improved EKF-SLAM algorithm with using Matlab isconducted. The result shows that effectiveness andprecision of the improved EKF-SLAM algorithm is higher than the traditional EKF-SLAM.
出处
《自动化与信息工程》
2014年第1期21-26,31,共7页
Automation & Information Engineering
