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精确稀疏扩展信息滤波的地图优化研究
引用本文:康丹,石守东,徐斌斌.精确稀疏扩展信息滤波的地图优化研究[J].宁波大学学报(理工版),2011,24(2):46-50.
作者姓名:康丹  石守东  徐斌斌
作者单位:宁波大学信息科学与工程学院,浙江宁波,315211
摘    要:研究了移动机器人同时定位与地图创建(SLAM)精确稀疏扩展信息滤波(ESEIF)的地图优化算法,即利用信息熵度量变量不确定性的特性来对地图特征点进行分类,选择不同类型的特征点处理ESEIF的不同更新过程,同时优化活动地图,使SLAM更新在恒定时间内实现,且提高了机器人和地图的估计精度.仿真实验证明:在特征点多的大环境下,特征点优化后的算法实时性强,估计精确度更高.

关 键 词:同时定位与地图构建  精确稀疏扩展信息滤波  信息熵  活动地图

Map Optimization of Exactly Sparse Extended Information Filter
KANG Dan,SHI Shou-dong,XU Bin-bin.Map Optimization of Exactly Sparse Extended Information Filter[J].Journal of Ningbo University(Natural Science and Engineering Edition),2011,24(2):46-50.
Authors:KANG Dan  SHI Shou-dong  XU Bin-bin
Institution:KANG Dan,SHI Shou-dong,XU Bin-bin(Faculty of Information Science and Technology,Ningbo University,Ningbo 325211,China)
Abstract:The Algorithm of map optimization about exactly sparse extended information filter(ESEIF) is investigated based on simultaneous localization and mapping(SLAM).It classifies the features of map exploiting the characteristic of information entropy which measure uncertainty of the variable,and choose different features to update corresponding process during ESEIF,and optimize the active maps at the same time.It updates SLAM in constant time,and it increases the estimation accuracy of the robot and map.Finally,...
Keywords:simultaneous localization and mapping  exactly sparse extended information filter  information entropy  active maps  
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