A Planer Moving Microphone Array for Sound Source Localization

Sound source localization (SSL) equips service robots with the ability to perceive sound similarly to humans, which is particularly valuable in complex, dark indoor environments where vision-based systems may not work. From a data collection perspective, increasing the number of microphones generally improves SSL performance. However, a large microphone array such as a 16-microphone array configuration may occupy significant space on a robot. To address this, we propose a novel framework that uses a structure of four planar moving microphones to emulate the performance of a 16-microphone array, thereby saving space. Because of its unique design, this structure can dynamically form various spatial patterns, enabling 3D SSL, including estimation of angle, distance, and height. For experimental comparison, we also constructed a circular 6-microphone array and a planar 4 × 4 microphone array, both capable of rotation to ensure fairness. Three SSL algorithms were applied across all configurations. Experiments were conducted in a standard classroom environment, and the results show that the proposed framework achieves approximately 80–90% accuracy in angular estimation and around 85% accuracy in distance and height estimation, comparable to the performance of the 4 × 4 planar microphone array.