Swarm Active Audition with Robots and Drones: Real-World Performance Validation

Kazuhiro Nakadai, Kotaro Hoshiba, Benjamin Yen, Makoto Kumon, Yoko Sasaki

Abstract: Search and rescue (SAR) operations in large-scale disaster sites, such as areas affected by earthquakes, require rapid victim detection. While drones equipped with cameras are commonly used for SAR, their effectiveness is limited in visually obstructed environments, because of debris, smoke, or fog. Under such situations, auditory information can play a crucial role in locating victims who are not visible. Existing drone audition research has demonstrated the feasibility of detecting sound sources using onboard microphone arrays. However, most studies focus on single-drone systems, which face limitations in coverage and accessibility, particularly in complex environments such as collapsed buildings or urban canyons. Additionally, real-world validation of multi-drone audition systems remains limited, with prior studies relying primarily on simulations or controlled environments. To address these challenges, we propose and evaluate a Multi-Drone and Robot-Based Active Audition System (SAAS-RD: Swarm Active Audition System with Robots and Drones) that integrates multiple drones and ground robots to enhance acoustic search capabilities. Our work focuses on real-world performance validation, conducting field experiments in outdoor environments and analyzing system feasibility through case studies. The results demonstrate the potential of SAAS-RD as a practical solution for large-scale SAR operations.

External IDs:dblp:conf/iros/NakadaiHYKS25