关键词: 扩展卡尔曼滤波, 模糊逻辑, 声纳, 定位, 新息

Abstract: To meet the requirement of accurate localization of mobile robot，a self-localization algorithm based on Fuzzy Kalman Filtering（FKF） is proposed.This paper employs an Extended Kalman Filtering（EKF） algorithm to fuse odometer readings and sonar data.To address the problem of performance degradation and even divergence of EKF caused by poor estimates of the observation noise，a fuzzy logic based adaption tuning algorithm，which can on-line adjust the observation noise covariance by monitoring the coincidence of the actual covariance with the theoretical covariance of residuals，is presented.Simulation results demonstrate that the proposed scheme achieves better localization precision and robustness than traditional EKF.

Key words: extended Kalman filtering, fuzzy logic, sonar, localization, residuals