一种改进的粒子滤波SLAM算法*

提出一种改进的粒子滤波SLAM（simultaneous localization and map building）同时定位和地图创建实现方法。改进方法让机器人大约行进10步完成基于局部已创建地图下的粒子滤波定位后，再利用激光传感器探测环境并更新创建的地图；同时在利用粒子滤波定位时，使粒子只分布在由航位推算法得出的机器人位姿附近，从而可有效地减少粒子的数量。实验结果表明，与标准的粒子滤波SLAM 算法比较，改进算法提高了机器人SLAM过程中定位和地图创建的精度和实时性，并为移动机器人在室外未知环境同时定位和地图创建提供了新方法。

Modified particle filter SLAM algorithm

This paper introduced an improved PF-SLAM (particle filtering-SLAM) approach.The improved method first let the robot run about ten steps and finished localizition based on the existing maps,and then used laser rangefinder to observe environments and updates maps.At the same time,in this method,particles were distributed only around the robot.The experiment results indicate that the precision and real-time performance of localization and mapping can be improved.It gives a new method for robot SLAM in outdoor unknown environments.