Adaptive extended Kalman filter (AEKF)-based mobile robot localization using sonar
作者： Qing-hao Meng , Yi-cai Sun , Zuo-liang Cao
DOI: 10.1017/S0263574700002605
关键词: Ekf algorithm 、 Extended Kalman filter 、 Artificial intelligence 、 Matching (graph theory) 、 Mobile robot 、 Process (computing) 、 Engineering 、 Computer vision 、 Sonar 、 Set (abstract data type)
摘要: In this paper, an AEKF algorithm is used to localize a mobile robot equipped with eight Polaroid sonars in indoor structured environment. The system state equation and sonar measurement models for locating the are set up. localization process based on given. Four criteria judge validity of predictive measurements presented, which can increase probability matching between actual measurements. Experiments show that precision our methods greater than using conventional EKF algorithm.
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