Abstract: Simultaneous Localization and Mapping（SLAM） is concerned to be the key point to realize the real autonomy of mobile robot.Unscented Kalman Filter（UKF） is widely applied in SLAM problem because of its directly using of nonlinear model.Concerning that square root filter can ensure non-negative definite of the covariance matrix.This article introduces square root unscented Kalman filter into SLAM problem and ensures its stability.This algorithm also gains a more accurate estimation compared to UKF based SLAM.Simulation results show that this algorithm is effective.

Key words: Simultaneous Localization and Mapping, Unscented Kalman filter, mobile robot

摘要： 同步定位与地图构建（SLAM）是移动机器人实现真正自主的关键，无迹卡尔曼滤波（UKF）由于直接利用系统非线性模型而在SLAM问题中得到广泛的应用。基于平方根滤波可以确保协方差矩阵的非负定的思想，将平方根UKF应用到SLAM问题中，确保了SLAM算法的稳定性，并得到了较高的估计精度。仿真结果表明，该算法是有效的。

关键词: 同步定位与地图构建, 无迹卡尔曼滤波, 移动机器人