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週刊ニュースレター購読
arXiv:2304.07596

Acoustic Beamforming for Object-relative Distance Estimation and Control in Unmanned Air Vehicles using Propulsion System Noise

Acoustic Beamforming for Object-relative Distance Estimation and Control in Unmanned Air Vehicles using Propulsion System Noise

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著者: Alisha Sharma, Jason Geder, Joseph Lingevitch, Theodore Martin, Daniel Lofaro, Donald Sofge

分類: cs.RO, cs.SD, eess.AS

原文アブストラクト

Unmanned air vehicles often produce significant noise from their propulsion systems. Using this broadband signal as "acoustic illumination" for an auxiliary sensing system could make vehicles more robust at a minimal cost. We present an acoustic beamforming-based algorithm that estimates object-relative distance with a small two-microphone array using the generated propulsion system noise of a vehicle. We demonstrate this approach in several closed-loop distance feedback control tests with a mounted quad-rotor vehicle in a noisy environment and show accurate object-relative distance estimates more than 2x further than the baseline channel-based approach. We conclude that this approach is robust to several practical vehicle and noise situations and shows promise for use in more complex operating environments.