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Constrained Submap Algorithm for Simultaneous Localization and Mapping

Constrained Submap Algorithm for Simultaneous Localization and Mapping
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摘要 When solving the problem of simultaneous localization and mapping(SLAM) ,a standard extended Kalman filter(EKF) is subject to linearization errors and causes optimistic estimation.This paper proposes a submap algorithm,which builds a weighted least squares(WLS) constraint between two adjacent submaps according to the different estimations of the common features and the relationship between the vehicle poses in the corresponding submaps.By establishing the constraint equation after loop closing,re-linearization is implemented and each submap's reference frame tends to its equilibrium position quickly.Experimental results demonstrate that the algorithm could get a globally consistent map and linearization errors are limited in local regions. When solving the problem of simultaneous localization and mapping (SLAM), a standard extended Kalman filter (EKF) is subject to linearization errors and causes optimistic estimation. This paper proposes a submap algorithm, which builds a weighted least squares (WLS) constraint between two adjacent submaps according to the different estimations of the common features and the relationship between the vehicle poses in the corresponding submaps. By establishing the constraint equation after loop closing, re-linearization is implemented and each submap's reference frame tends to its equilibrium position quickly. Experimental results demonstrate that the algorithm could get a globally consistent map and linearization errors are limited in local regions.
出处 《Journal of Shanghai Jiaotong university(Science)》 EI 2009年第5期600-605,共6页 上海交通大学学报(英文版)
基金 the Knowledge Innovation Program of Shanghai Science and Technology Committee (No.08510708300) the Ph.D.Programs Foundation of Ministry of Education of China (No.20070248097)
关键词 simultaneous localization and mapping (SLAM) CONSISTENCY submap weighted least squares (WLS) 图算法 地图 定位 加权最小二乘法 扩展卡尔曼滤波器 线性误差 SLAM 共同特征
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