A 4-channel acoustic sensor system for sound source detection of the service robot

Constrained by the physical geometry of microphone arrays on the service robot, there exist limitations on both the minimum and maximum frequency bounds along with the coverage area. While the mobility of a microphone array carried by a robot offers the potential for a broader operational frequency range and a more comprehensive perspective, achieving this necessitates a practically more extensive and densely packed array configuration. This is often accomplished by employing non-synchronous measurements in beamforming. Here, we propose a novel approach for locating broadband sound sources using an asynchronous measurement technique that employs Laplacian-enhanced low-rank tensor completion. Our technique analyzes the tensor data structure within broadband signals and incorporates an alternating-direction approach based on multiplier optimization. Through the simulation study using only four physical channels, our Laplacian-enhanced algorithm has demonstrated the ability to generate a highly accurate sound map capturing distinct speech signal sources, thus providing a superior global view compared to the alternative convex surrogate. This advancement holds substantial promise for applications in which precise localization of broadband sound sources is paramount.