A New Method of Simultaneous Localization and Mapping for Mobile Robots Using Acoustic Landmarks

Abstract

The simultaneous localization and mapping (SLAM) problem for mobile robots has always been a hotspot in the field of robotics. Simultaneous localization and mapping for robots using visual sensors and laser radar is easily affected by the field of view and ground conditions. According to the problems of traditional sensors applied in SLAM, this paper presents a novel method to perform SLAM using acoustic signals. This method enables robots equipped with sound sources, moving within a working environment and interacting with microphones of interest, to locate itself and map the objects simultaneously. In our case, a method of microphone localization based on a sound source array is proposed, and it was applied as a pre-processing step to the SLAM procedure. A microphone capable of receiving sound signals can be directly used as a feature landmark of a robot observation model without feature extraction. Meanwhile, to eliminate the random error caused by hardware equipment, a sound settled in the middle of two microphones was applied as a calibration sound source to determine the value of the random error. Simulations and realistic experimental results demonstrate the feasibility and effectiveness of the proposed method.