Multi Agent Switching Mode Controller for Sound Source localization

2025-10-16

AI Summary

This paper addresses the challenge of multi-agent acoustic source localization under non-line-of-sight (NLoS) conditions. We propose a distributed localization framework integrating acoustic sensor fusion with mode-switching control. Methodologically, we design an adaptive multi-agent switching control mechanism: in single-source scenarios, agents maintain a rigid formation to collaboratively advance and enhance localization accuracy; in multi-source scenarios, they switch to independent optimization to improve source resolution. By unifying distributed acoustic field sensing, formation control, and switching system theory, the framework ensures smooth, theoretically grounded transitions between operational modes. Experimental results demonstrate high robustness and localization efficiency for both single- and multi-source configurations in complex environments. The approach significantly improves system flexibility, environmental adaptability, and search effectiveness compared to conventional fixed-mode strategies.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Search and Optimization: Mixed Discrete/Continuous Search
• Multiagent Systems: Distributed Problem Solving

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

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.

Problem

• Developing multi-agent control for acoustic source localization
• Enabling target seeking without direct line of sight
• Addressing both single-source and multi-source scenarios

Innovation

• Multi-agent switching mode control strategy
• Acoustic-based target localization approach
• Rigid formation and independent search modes