Acoustic SLAM based on the Direction-of-Arrival and the Direct-to-Reverberant Energy Ratio

TL;DR

This paper introduces a novel acoustic SLAM method that combines DoA and DRR measurements with inertial data, enabling accurate indoor localization and mapping in challenging environments like foggy disaster zones.

Contribution

It presents the first real-world validation of an acoustic SLAM algorithm using only acoustic data and IMU, integrating DRR for source distance estimation and a keyframe approach for improved accuracy.

Findings

Average location accuracy of 0.48 m

Source position error converges to <0.25 m within 2.8 s

Effective in real-world indoor scenes for search and rescue

Abstract

This paper proposes a new method that fuses acoustic measurements in the reverberation field and low-accuracy inertial measurement unit (IMU) motion reports for simultaneous localization and mapping (SLAM). Different from existing studies that only use acoustic data for direction-of-arrival (DoA) estimates, the source's distance from sensors is calculated with the direct-to-reverberant energy ratio (DRR) and applied as a new constraint to eliminate the nonlinear noise from motion reports. A particle filter is applied to estimate the critical distance, which is key for associating the source's distance with the DRR. A keyframe method is used to eliminate the deviation of the source position estimation toward the robot. The proposed DoA-DRR acoustic SLAM (D-D SLAM) is designed for three-dimensional motion and is suitable for most robots. The method is the first acoustic SLAM algorithm that has been validated on a real-world indoor scene dataset that contains only acoustic data and IMU measurements. Compared with previous methods, D-D SLAM has acceptable performance in locating the robot and building a source map from a real-world indoor dataset. The average location accuracy is 0.48 m, while the source position error converges to less than 0.25 m within 2.8 s. These results prove the effectiveness of D-D SLAM in real-world indoor scenes, which may be especially useful in search and rescue missions after disasters where the environment is foggy, i.e., unsuitable for light or laser irradiation.