Audio-Based Search and Rescue with a Drone: Highlights from the IEEE Signal Processing Cup 2019 Student Competition

Antoine Deleforge 1 Diego Di Carlo 2 Martin Strauss 3 Romain Serizel 1 Lucio Marcenaro 4
1 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
2 PANAMA - Parcimonie et Nouveaux Algorithmes pour le Signal et la Modélisation Audio
Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : Increasing interest in unmanned aerial vehicles (UAVs), commonly referred to as drones, has occurred in recent years. Search and rescue scenarios where humans in emergency situations need to be quickly found in difficult-toaccess areas constitute an important field of application for this technology. Drones have already been used by humanitarian organizations in countries such as Haiti and the Philippines to map areas after a natural disaster using high-resolution embedded cameras, as documented in a recent United Nations report [1]. Although research efforts have focused mostly on developing video-based solutions for this task [2], UAV-embedded audio-based localization has received relatively less attention [3]?[7]. However, UAVs equipped with a microphone array could be of critical help to localize people in emergency situations, especially when video sensors are limited by a lack of visual feedback due to bad lighting conditions (such as at night or in fog) or obstacles limiting the field of view (Figure 1).
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Antoine Deleforge, Diego Di Carlo, Martin Strauss, Romain Serizel, Lucio Marcenaro. Audio-Based Search and Rescue with a Drone: Highlights from the IEEE Signal Processing Cup 2019 Student Competition. IEEE Signal Processing Magazine, Institute of Electrical and Electronics Engineers, 2019, 36 (5), pp.138-144. ⟨10.1109/MSP.2019.2924687⟩. ⟨hal-02161897⟩

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