Multi Agent Switching Mode Controller for Sound Source localization

TL;DR

The paper addresses robust acoustic source localization with multiple agents under limited visibility by proposing a switching mode controller that alternates between listening/estimation and movement. A recursive Bayesian estimation framework fuses DoA and step-length measurements, while a hybrid system governs when agents listen or move. For a single source, a bearing-rigid four-agent formation guides the centroid toward the target; for multiple sources, agents explore independently and share detections to improve coverage. Simulations demonstrate the approach's resilience to noise and its capacity to detect multiple sources, highlighting potential for search-and-rescue applications and challenging environments. Overall, the work advances multi-agent sound localization by integrating RBE with a switching control strategy and exploration mechanisms that adapt to the presence of one or many sources.

Abstract

Source seeking is an important topic in robotic research, especially considering sound-based sensors since they allow the agents to locate a target even in critical conditions where it is not possible to establish a direct line of sight. In this work, we design a multi- agent switching mode control strategy for acoustic-based target localization. Two scenarios are considered: single source localization, in which the agents are driven maintaining a rigid formation towards the target, and multi-source scenario, in which each agent searches for the targets independently from the others.

Figures (4)

• Figure 1: Four agents bearing rigid formation
• Figure 2: Formation behaviour ($\sigma_d^2 = 0.1$, $k_{\theta} = 1$)
• Figure 3: Formation's centroid distance from the target ($\sigma_d^2 = 0.1$, $k_{\theta} = 1$)
• Figure 4: Real targets (in black) and detected targets (in blue)