基于激光扫描测距的机器人粒子滤波定位技术研究  

Research on robot particle filtering localization technology based on laser scanning ranging

作　　者：戈广双 李子龙 杨凯[1] 马瑞鑫 

机构地区：[1]交通运输部天津水运工程科学研究所,天津300000

出　　处：《传感器与微系统》2017年第12期36-39,共4页Transducer and Microsystem Technologies

基　　金：中央级公益性科研院所基本科研业务费项目(TKS160212)

摘　　要：传统的粒子滤波即时定位与地图构建(SLAM)算法在构建地图和目标进行自主定位时,粒子数量大,占用的内存高,重采样之后容易出现粒子匮乏现象,为了提高机器人自主定位的效率,提出了一种改进的重采样策略和粒子更新策略,融入系统模型。在装有机器人操作系统(ROS)的旅行家移动机器人上进行测试,实验结果表明:方法能够有效提升粒子滤波定位的效率。The traditional particle filtering simultaneous localization and mapping（ SLAM） algorithm in the construction of mapping and autonomous positioning,usually need large number of particles and take up a lot of memory,particles appear deprivation after the resampling process,in order to improve the efficiency of robot autonomous positioning,aiming at particle filtering algorithm,propose an improved resampling strategy and particle update strategy,fuse system model. By testing the algorithm on a mobile robot equipped with robot operating system（ ROS）,the algorithm is validated by experimental method. The experimental results show that the method can improve the efficiency of particle filtering positioning.

关 键 词：即时定位与地图构建 粒子滤波 蒙特卡洛定位算法 机器人操作系统 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]