A Wavelet Transform Assisted Extended Kalman Filter-Based Approach for Simultaneous Localization and Mapping Problems

作者：Xiao Benjie; Xu Kai; Zhao Yilu; Chen Xiong^*

来源：Sensor Letters, 2012, 10(8): 1814-1818.

DOI：10.1166/sl.2012.2615

• Simultaneous Localization and Mapping (SLAM) Problem
• Wavelet Transform Assistance
• Extended Kalman Filter (EKF)
• Sensor Statistics

Extended Kalman filter (EKF) has been a popular choice to solve simultaneous localization and mapping (SLAM) problems for mobile robots or vehicles. However, the performance of the EKF depends on the correct a priori knowledge of process and measurement noise covariance matrices (Q and R, respectively). The present paper proposes a wavelet transform assisted extended Kalman filter-based approach for simultaneous localization and mapping problems (WTEKF-SLAM), which attempts to estimate the elements of the R matrix of the EKF algorithm through wavelet transform in situations where measurement noise covariance (R) is incorrect. Simulated results have demonstrated that the proposed WTEKF-SLAM approach outperforms the EKF-SLAM approach and the NFEKF-SLAM approach (a neuro-fuzzy assisted adaption of EKF-SLAM approach) when measurement noise covariance is incorrect.

• 出版日期2012-12
• 单位复旦大学