The Effect of Acoustic Detection Constraints on Optimizing Drones' Delivery Missions

Airborne package deliveries in urban and rural environments via drone platforms such as multi-rotors have become a fast-evolving market in general aviation over the past decade. Despite numerous advantages (e.g., maneuverability, low cost, etc.), multi-rotor platforms result in a significant acoustic pollution penalty produced by the harsh and distinctive sound emitted by the rotors, which is already adversely affecting the health of many residential communities. Since drone noise regulations are frequently discussed, a growing need emerges for advanced multi-rotor mission planning tools incorporating acoustic detection constraints. This paper presents a novel mission planning framework to solve the multi-rotor delivery service problem, combining navigation planning and acoustic constraints for the surrounding communities to yield a low-noise signature and optimal delivery route. The mission planning algorithm employs a global optimization approach, performing an optimal graph search over key points from delivery to destination, obtained by analyzing the Digital Terrain Map (DTM) and the acoustic constraints evaluated by the psychoacoustic metric of loudness. The mission planning framework presented herein demands low computational resources and thus has the potential to be integrated into a drone's flight computer for real-time mission planning in the future.