%0 Journal Article %T Connectionist approach for cognitive map learning and navigation based on spatio-temporal experiences
一种基于连接机制和时空经验的认知地图学习与导航方法 %A LIU Juan %A CAI Zi-xing %A TU Chun-ming %A
刘 娟 %A 蔡自兴 %A 涂春鸣 %J 控制理论与应用 %D 2003 %I %X A connectionist method is proposed for mobile robot, which lacks a priori environmental model and global localization information, to learn goal directed cognitive map from its own spatio temporal experiences. Temporal sequence processing network (TSPN), which is constructed at run time, provides compact representations of history perceptive information, transforms spatial knowledge into cell firing characteristics and retrieves them in later runs to guide the robot. The navigation system integrating TSPN and a reactive safeguard module performs dynamic landmark and heading detection, route learning and collision free real time navigation in noisy environments. The simulation and real world experiments demonstrate the effectiveness and flexibility of the system. %K connectionist model %K spatio temporal reasoning %K mobile robot %K cognitive map %K navigation
连接机制模型 %K 时空推理 %K 移动机器人 %K 认知地图 %K 导航 %U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=AE76E4BA856C72CE&yid=D43C4A19B2EE3C0A&vid=A04140E723CB732E&iid=0B39A22176CE99FB&sid=8575BEDA702C4B7C&eid=ED01F5AE50BE09C0&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=8