Unmanned aerial vehicles (UAV), commonly referred to as drones, have raised increasing interest in recent years. Search and rescue scenarios where humans in emergency situations need to be quickly found in areas difficult to access constitute an important field of application for this technology. While research efforts have mostly focused on developing video-based solutions for this task \cite{lopez2017cvemergency}, UAV-embedded audio-based localization has received relatively less attention. Though, UAVs equipped with a microphone array could be of critical help to localize people in emergency situations, in particular when video sensors are limited by a lack of visual feedback due to bad lighting conditions or obstacles limiting the field of view. This motivated the topic of the 6th edition of the IEEE Signal Processing Cup (SP Cup): a UAV-embedded sound source localization challenge for search and rescue. In this article, we share an overview of the IEEE SP Cup experience including the competition tasks, participating teams, technical approaches and statistics.
@article{arxiv.1907.04655,
title = {Audio-Based Search and Rescue with a Drone: Highlights from the IEEE Signal Processing Cup 2019 Student Competition},
author = {Antoine Deleforge and Diego Di Carlo and Martin Strauss and Romain Serizel and Lucio Marcenaro},
journal= {arXiv preprint arXiv:1907.04655},
year = {2019}
}