中原工学院学报

针对植保无人机在多个地块间执行喷洒任务的作业次序规划问题，建立农药喷洒任务的最小化飞行里程目标函数。考虑长距离作业下的载重和续航约束，采用改进的蚁群算法求解该目标函数。通过对启发式函数与挥发系数进行改进，并对挥发系数的下限进行限制，避免了算法陷入局部最优解。仿真结果表明，相比标准蚁群算法，采用所提出的改进蚁群算法，在飞行总里程上缩短了6.2%,且具有更强的路径寻优能力，对作业次序的规划也更加合理。

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.