基于FastSLAM的RoboCup家庭组机器人自定位方法研究  

Study on Self-localization System of RoboCup@Home Robot Based on FastSLAM

作　　者：宋鑫坤[1] 陈万米[1,2] 徐昱琳[1,2] 朱明[1] 张雷[1] 

机构地区：[1]上海大学机电工程与自动化学院,上海200072 [2]上海市电站自动化技术重点实验室,上海200072

出　　处：《系统仿真学报》2009年第21期6781-6785,共5页Journal of System Simulation

基　　金：上海市重点学科建设项目(T0103)

摘　　要：FastSLAM算法为机器人定位与地图构建开辟了新的研究方向,研究该理论在RoboCup家庭组机器人自定位系统上的应用。从贝叶斯滤波理论,Rao-Blackwellised解耦,粒子滤波器原理等方面论述了FastSLAM的关键技术及基本理论。针对家庭组机器人非结构化场景的特殊情况,提出基于FastSLAM的定位策略。仿真结果表明算法的有效性和鲁棒性,能够为家庭机器人在非结构化场景中的定位问题提供有效地解决方案。FastSLAM theory has opened a new research direction for robot localization and mapping, and its application on Self-Localization System of RoboCup@Home Robot was studied. The key technology and basic theory of FastSLAM were covered from aspects of Bayes filter theory, Rao-Blackwellised factorization and particle filter. A localization method based FastSLAM was proposed, specifically to the unstructured scenes for RoboCup@Home Robot. Simulation results prove the effectiveness and robustness of the method which can provide effective solution for the self-localization problem of RoboCup @Home Robot under unstructured scenes.

关 键 词：FASTSLAM RoboCup家庭组机器人 自定位 非结构化场景 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]