Abstract

With the development of aviation agricultural technology, the number of farmers adopting the use of drones in daily agricultural activities is growing rapidly in recent decades. Among these, a large portion constitutes agricultural drones being used in pest control and crop protection practices, e.g. agriculture spraying of pesticides. Spraying pesticides with drones have proven to be faster than other traditional methods. On the downside, flight time and range of Unmanned Aerial Vehicles (UAV) are often limited. Thus, a proper arrangement of flight height and velocity will greatly improve spraying efficiency. A new strategy to optimize the flight parameters, i.e. flight height and flight velocity, for fixed-wing UAV with a 3D simulation-based approach together with an automatic optimization algorithm was proposed in this study. To find the optimal parameters for a UAV to fly and spray under certain environmental conditions, a three-dimensional model of the target crop was established first, followed by a detailed simulation of droplet spraying. As a demonstration case, a grass model was developed and used as the target plant, and a physics-based method was used to simulate realistically the movement of the droplets in the air as well as the interaction between the droplets and the plant to obtain the droplet deposition rate under the specified operating parameters. Furthermore, the standard Particle Swarm Optimization (PSO) algorithm was used to optimize the UAV operating parameters to obtain the best operating parameters. The results indicate that using the standard PSO algorithm to optimize the operating parameters of the drone could significantly improve the deposition rate and find the best operating parameters. Keywords: unmanned aerial vehicle, droplet deposition, 3D simulation, particle swarm optimization algorithm DOI: 10.25165/j.ijabe.20231601.6581 Citation: Xu L F, Yang Z Z, Huang Z S, Ding W L, Buck-Sorlin G. Effects of flight parameters for plant protection UAV on droplets deposition rate based on a 3D simulation approach. Int J Agric & Biol Eng, 2023; 16(1): 66–72.

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