基于时变调节因子的移动机器人EKF-SLAM算法

EKF-SLAM Algorithm Based on Time Varying Regulation Factor

移动机器人路径规划问题一直是机器人控制领域中的热点.提出基于时变调节因子的EKF-SLAM(扩展卡尔曼滤波的同时定位与地图构建)算法,使移动机器人在定位和构建地图的同时,在生成的地图环境中可以很好地选择最优或者较优路径.该方法将强跟踪滤波器与EKF-SLAM相结合,引入时变调节因子,可以根据运动状态引起的新息权重的大小而改变,从而决定增大或减小滤波增益,进一步提高状态估计精度.实验证明该算法与传统算法相比,具有更好鲁棒性且误差更小.

The problem of mobile robot path planning has been a hot research topicontrol.An improved EKF-SLAM algorithm is proposed in this paper.Mobile robots canor better path in the generated map environment while locating and constructing the m a p . T h e strong tracking filter is combined with EKF-SLAM algorithm in the presented m e t h o d,a time-varying weight adjustment factor is introduced？which can be changed according to the Innovation weighted value caused by the motion state,so as to increase or decrease the filter gain and further improve the state estimation accuracy.The simulation results s how that the presented algorithm has better robustness and the error is smaller than traditional algorithm.