Visual Localization in Urban Area Using Orthogonal Building Boundaries and a GIS Database  

作　　者：LI Haifeng LIU Jingtai LU Xiang 

机构地区：[1]Civil Aviation University of China, Tianjin 300300, China [2]Institute of Robotics and Automatic Information System, Nankai University, Tianjin 300071, China

出　　处：《机器人》2012年第5期604-613,619,共11页Robot

基　　金：National Nature Science Foundation of China(60905061)

摘　　要：A framework is presented for robustly estimating the location of a mobile robot in urban areas based on images extracted from a monocular onboard camera, given a 2D map with building outlines with neither 3D geometric information nor appearance data. The proposed method firstly reconstructs a set of vertical planes by sampling and clustering vertical lines from the image with random sample consensus (RANSAC), using the derived 1D homographies to inform the planar model. Then, an optimal autonomous localization algorithm based on the 2D building boundary map is proposed. The physical experiments are carried out to validate the robustness and accuracy of our localization approach.A framework is presented for robustly estimating the location of a mobile robot in urban areas based on images extracted from a monocular onboard camera, given a 2D map with building outlines with neither 3D geometric information nor appearance data. The proposed method firstly reconstructs a set of vertical planes by sampling and clustering vertical lines from the image with random sample consensus （RANSAC）, using the derived 1D homographies to inform the planar model. Then, an optimal autonomous localization algorithm based on the 2D building boundary map is proposed. The physical experiments are carded out to validate the robustness and accuracy of our localization anoroach.

关 键 词：机器人 设计 人工智能 信息处理 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] TP391[自动化与计算机技术—控制科学与工程]