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自主机器人SLAM改进算法 被引量：1

Improved SLAM Algorithm Research on Autonomous Rover
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摘要 SLAM(Simultaneous Localization and Mapping,同时定位与地图创建)可以看成同时估计机器人和障碍物位置的问题,SLAM应用于未知环境的的主要困难之一就是这两个估计问题之间的强耦合。围绕这个问题提出了融合SLAM这两个估计的协方差交叉优化算法,解决了SLAM常用滤波算法易受到数据相关性困扰的问题。 Simultaneous Localization and Mapping is the way to estimate the location of the robot and mapping at the same time. The main difficulty to use this way in an unknown environment is the strong coupling between the estimate of the robot and the landmarks. According to this, a covariance Intersection optimal algorithm is put forward, in order to solve the problem of data association in SLAM filter algorithm.
作者 曹梦龙 崔平远
机构地区 青岛科技大学自动化与电子工程学院 哈尔滨工业大学深空探测基础研究中心
出处 《青岛科技大学学报（自然科学版）》 CAS 2008年第4期361-365,共5页 Journal of Qingdao University of Science and Technology:Natural Science Edition
关键词 自主机器人 SLAM 数据相关 交叉协方差 autonomous robot SLAM data association covariance intersection
分类号 TP242 [自动化与计算机技术—检测技术与自动化装置]
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参考文献12

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二级参考文献32

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共引文献59

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青岛科技大学学报（自然科学版）
2008年 第4期

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