%0 Journal Article
%T Omnidirectional Vision-based Self-localization by Using Large-scale Metric-topological 3D Map<br>基于几何－拓扑广域三维地图和全向视觉的移动机器人自定位
%A WANG Ke
%A WANG Wei
%A ZHUANG Yan
%A SUN Chuan-Yu
%A <br>王珂
%A 王伟
%A 庄严
%A 孙传昱
%J 自动化学报
%D 2008
%I 
%X Towards large-scale indoor environment, a novel metric-topological 3D map is proposed for robot self- localization based on omnidirectional vision. The local metric map, in a hierarchical manner, defines geometrical elements according to their environmental feature levels. Then, the topological parts in the global map are used to connect the adjacent local maps. We design a nonlinear omnidirectional camera model to project the probabilistic map elements with uncertainty manipulation. Therefore, image features can be extracted in the vicinity of corresponding projected curves. For the self-localization task, a human-machine interaction system is developed using a hierarchical logic. It provides a fusion center which adopts feedback hierarchical fusion method to fuse local estimates generated from multi-observations. Finally, a series of experiments are conducted to prove the reliable and practical performance of our system.
%K Self-localization
%K hybrid metric--topological 3D map
%K omnidirectional vision
%K human-machine interaction<br>自定位
%K 几何–拓扑混合三维地图
%K 全向视觉
%K 人机交互
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=367E94426D8F17B04E1728D5CAD849B2&yid=67289AFF6305E306&vid=339D79302DF62549&iid=708DD6B15D2464E8&journal_id=0254-4156&journal_name=自动化学报&referenced_num=2&reference_num=22