[1]涂刚毅,金世俊,祝雪芬,等.基于粒子滤波的移动机器人SLAM算法[J].东南大学学报(自然科学版),2010,40(1):117-122.[doi:10.3969/j.issn.1001-0505.2010.01.022]
 Tu Gangyi,Jin Shijun,Zhu Xuefen,et al.Particle filter SLAM method for mobile robot[J].Journal of Southeast University (Natural Science Edition),2010,40(1):117-122.[doi:10.3969/j.issn.1001-0505.2010.01.022]
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基于粒子滤波的移动机器人SLAM算法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
40
期数:
2010年第1期
页码:
117-122
栏目:
自动化
出版日期:
2010-01-20

文章信息/Info

Title:
Particle filter SLAM method for mobile robot
作者:
涂刚毅 金世俊 祝雪芬 宋爱国
东南大学仪器科学与工程学院,南京 210096
Author(s):
Tu Gangyi Jin Shijun Zhu Xuefen Song Aiguo
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
关键词:
移动机器人 同步定位与地图创建 粒子滤波器 栅格地图
Keywords:
mobile robot simultaneous localization and mapping particle filter grid map
分类号:
TP242
DOI:
10.3969/j.issn.1001-0505.2010.01.022
摘要:
针对FastSLAM算法对传感器精度要求较高,不适用于方向性差的超声传感器问题,提出了一种基于超声概率栅格地图环境特征点提取匹配的移动机器人粒子滤波同时定位与地图创建(SLAM)算法.该算法可分解为机器人位姿估计和环境路标估计2个部分.基于蒙特卡罗定位原理利用粒子滤波算法对机器人运动轨迹进行估计; 在建立全局超声概率栅格地图的基础上,利用概率栅格地图环境特征提取算法对环境路标坐标进行估计.实验证明,该算法较好地解决了超声测距传感器由于散射角大带来的特征点估计不准的问题,对环境路标和机器人轨迹的估计都比较准确.并对移动机器人累计误差进行了有效的补偿,减少了由于累积误差造成的移动机器人轨迹扭曲失真.
Abstract:
Focusing on the limited application of FastSLAM algorithm due to its high accuracy requirment for sensor and unfitness for ultrasonic sensor with poor directivity, a simultaneous localization and mapping(SLAM)algorithm utilizing particle filter is provided, which is based on ultrasonic probability grid map feature points extraction and matching. This algorithm consists of robot pose estimation and environment landmark estimation. Particle filters are applied to estimate the robot trajectory according to Monte Carlo methods. Based on global ultrasonic probabilistic grid map, the environment landmark position is observed by environment feature extraction algorithm. The effectiveness of the proposed algorithm is validated by experimental result. The estimation accuracy of feature point position as well as environment landmark are improved. The cumulative error of the robot is compensated effectively and the mobile robot trajectory distortion is reduced.

参考文献/References:

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备注/Memo

备注/Memo:
作者简介: 涂刚毅(1981—),男,博士生; 金世俊(联系人),男,博士,副教授,jinsj@263.net.
基金项目: 教育部高等学校科技创新工程重大项目培育资金项目(708045)、江苏省“六大高峰人才”资助项目(06-D-031)、东南大学优秀青年教师基金资助项目(4022001004).
引文格式: 涂刚毅,金世俊,祝雪芬,等.基于粒子滤波的移动机器人SLAM算法[J]. 东南大学学报:自然科学版,2010,40(1):117-122.[doi:10.3969/j.issn. 1001-0505.2010.01.022]
更新日期/Last Update: 2010-01-20