Acoustic SLAM With Moving Sound Event Based on Auxiliary Microphone Arrays

Abstract

Acoustic simultaneous localization and mapping (ASLAM) aim to map the positions of sound sources while passively localizing the microphone array embedded in the robot platform. In this paper, an ASLAM method with auxiliary microphone arrays based on dual interacting multiple models and unscented Kalman filter (D-IMM-UKF) is proposed for the single moving source scenario. Firstly, a dual-unscented Kalman filter is presented, which can simultaneously track the robot and the speaker. Then, the interacting multiple models are adopted for the different motion dynamics of a robot and a speaker in space. To avoid the underdetermined condition when only the acoustic information is available, a small number of static microphone arrays are employed. Finally, the moving robot’s and speaker’s positions are estimated by the D-IMM-UKF algorithm. It can obtain the trajectories of the robot’s and speaker’s movements smoothly with good tracking accuracy. Experimental results verify the effectiveness of the proposed method.