Research on task allocation for agricultural UAVs based on improved ant colony optimization algorithm
ZHOU Xinpeng
ZHANG Limin
HU Bohao
WANG Zonghui
TAN Donghai
CHANG Zhina
Abstract：To address the problem of operation sequence planning for plant protection drones to perform spraying tasks among multiple plots,the objective function of minimizing flight mileage for pesticide spraying tasks is established.Considering the load and endurance constraints under long-distance operation,an improved ant colony algorithm is proposed to solve this objective function.By improving the heuristic function and the volatility coefficient and restricting the lower limit of the volatility coefficient,the slow convergence of the algorithm can be avoided.The simulation results show that,compared with the traditional ant colony algorithm,the proposed improved ant colony algorithm optimizes the total flight mileage by 6.2％,and has a stronger path optimization ability and a more efficient planning of the operation sequence.
Keywords：intelligent agricultureplant protection dronepath planningimproved ant colony optimizationtask allocation
Publication Date：2025-08-25
Online Publishing Date：2025-09-25(First online date of this platform, not the publication date of the document)
Pages：5( 11-15 )