中文摘要：

在移动机器人同时定位与地图创建（SLAM）过程中,机器人本身位置不确定,其所处环境也不可预知,针对这些不确定性因素,应用贝叶斯规则作为理论基础,建立移动机器人SLAM算法的概率表示模型,通过扩展卡尔曼滤波器实现SLAM算法,并介绍一种激光雷达数据与特征地图的数据关联方法。实验结果表明,该方法为实现SLAM算法提供了一种有效可靠的途径。

英文摘要：

During the mobile robot Simultaneous Localization And Mapping（SLAM）,the location is unknown and the environment round is also unpredictable. Aiming at these uncertain factors,the Bayes rule is as a theory foundation,the probability model of the mobile robot SLAM is founded,the realization process of the SLAM by Extended Kalman Filter（EKF） is discussed. A data association method between the laser radar and the feature map is introduced. Experimental results show this method is effective and reliable to realize SLAM.