多植保无人机协同路径规划

doi:10.7527/S1000-6893.2019.23610

Abstract

Abstract: In order to achieve collaborative work and improve operation efficiency of multi-sprayer-Unmanned Aerial Vehicles(UAVs), a cooperative path planning algorithm for multi-sprayer-UAVs based on the improved Particle Swarm Optimization(PSO) is proposed. Considering the working area’s shape and size and the operating parameters of sprayer-UAV, the working area of each UAV is divided. The full coverage route in each area is generated by grid method. The operation distance during one trip of each sprayer-UAV is used as the algorithm optimization variable. Under the condition that the replenishment time of each UAV meets the interval distribution constraint, four factors of replenishment frequency, total replenishment time, total operation time and minimum replenishment interval are comprehensively considered, constituting the objective function. The improved PSO algorithm is applied to optimize the position of return points and return sequence of UAVs. The simulation results show that compared with the maximum operating distance planning and the minimum return distance planning, the proposed planning alqorithm show better performance and better operation area adaptability, which proved its effectiveness and practicability.

Key words: path planning, multi-sprayer-Unmanned Aerial Vehicle(UAV), supply point, Particle Swarm Optimization(PSO), return points

CLC Number:

V279
S252

KAN Ping, JIANG Zhaoliang, LIU Yuhao, WANG Zhenwu. Cooperative path planning for multi-sprayer-UAVs[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(4): 323610-323610.

References 21

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Cooperative path planning for multi-sprayer-UAVs

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