A Hybrid PSO algorithm based Flight Path Optimization for Multiple Agricultural UAVs

Unmanned aerial vehicles (UAVs) has shown an increasing interests in agricultural applications. However, single UAV is considered impractical for its limited flight endurance. In this paper, A VND (Variable Neighborhood Descend) enhanced Genetic-PSO (Particle Swarm Optimization) algorithm is applied to optimize the flight paths for a group of Multiple agricultural UAVs. Instead of minimizing the total flight distance (approach A), the objective of our method is to optimize the flight paths of the whole UAVs group with minimum make-span (approach B). Both approaches have been verified respectively in two agricultural regions of Shaanxi Province. The comparative results show that our proposed method (approach B) effectively reduced the UAVs group's flight time and make it better serve the precision agriculture.