Quaternion-Based Acoustic SLAM for 3D Drone Localization and Source Mapping

Abstract

Accurate localization and mapping are challenging in environments with poor visibility or noise interference, such as underwater, at night, or in fog, where visual data are unreliable or limited. We present an approach to enhance 3D drone localization and sound mapping using acoustic Simultaneous Localization and Mapping. This method incorporates Angle of Arrival and Time Difference of Arrival measurements of sound sources, as well as quaternions to represent orientation. We simulate a drone equipped with three receiver stations to map multiple stationary sound sources, along with an inertial measurement unit for drone localization. This paper shows drone localization and source mapping using only acoustic and inertial measurements.