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基于稀疏扩展信息滤波的同步定位与地图创建算法研究
发表时间:2008-05-31 浏览量:2740 下载量:936
全部作者: | 李久胜,王要强,李永强 |
作者单位: | 哈尔滨工业大学电气工程及自动化学院 |
摘 要: | 本文针对传统扩展卡尔曼滤波(extended Kalman filter,EKF)方法对机器人同步定位与地图创建(simultaneous localization and map building,SLAM)中计算复杂度大的问题,提出了一种基于稀疏扩展信息滤波(sparse extended information filter,SEIF)的SLAM算法。通过稀疏化信息矩阵,使复杂度得到有效降低。仿真结果表明该算法计算复杂度与地图中的环境特征个数无关,可以实现恒时执行,在计算时间和占用内存上远远优于EKF,尤其适用于处理复杂环境下大地图的自主机器人SLAM的问题。 |
关 键 词: | 电力电子与电力传动;机器人导航;同步定位与地图创建;稀疏扩展信息滤波 |
Title: | SLAM based on sparse extended information filter |
Author: | LI Jiusheng, WANG Yaoqiang, LI Yongqiang |
Organization: | School of Electrical Engineering & Automation, Harbin Institute of Technology |
Abstract: | Aiming at the significant computational burden of the traditional EKF-SLAM, a novel algorithm, SLAM based on SEIF(sparse extended information filter) is proposed. Through sparsification of the information matrix, computational complexity can be reduced notably. Simulation results show that SEIF-SLAM can be executed in constant time, irrespective of the size of the map, and have a better performance than EKF-SLAM on CPU time and memory usage, especially in the large map and complex environment. |
Key words: | power electronics and electric drives; robot navigation; simultaneous localization and map building(SLAM); sparse extended information filter(SEIF) |
发表期数: | 2008年9月第10期 |
引用格式: | 李久胜,王要强,李永强. 基于稀疏扩展信息滤波的同步定位与地图创建算法研究[J]. 中国科技论文在线精品论文,2008,1(10):1200-1206. |

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