Journal of Civil Aviation University of China ›› 2025, Vol. 43 ›› Issue (1): 89-96.

• General aviation and drones • Previous Articles    

Route planning of urban logistics UAV based on improved artificial fish
swarm algorithm

YUE Rentian1 , HOU Bowen2
  

  1. 1. College of Air Traffic Management, CAUC, Tianjin 300300, China; 2. Institute of New Navigation, China Academy of
    Civil Aviation Science and Technology, Beijing 100028, China 
  • Received:2024-03-29 Revised:2024-05-14 Online:2025-04-09 Published:2025-04-09

Abstract:

In order to safely and efficiently solve the problem of three-dimensional spatial route planning for logistics unmanned aerial vehicles (UAV), this paper first models the planning environment by improving the grid method
based on spatial obstacle avoidance and ground population density. The route planning model for logistics UAV is
established with the objective function of minimizing the sum of distance cost, grid risk value cost and height adjustment cost, and constraints are set according to UAV performance. Secondly, the standard artificial fish swarm
algorithm (AFSA) is improve by adding fish swarm jumping behavior and grid taboo table, and the improved AFSA
is employed to solve the model. Finally, the improved AFSA was compared with three other algorithms through
simulation examples and parameter sensitivity analysis was conducted on the improved AFSA. The results show
that the improved AFSA had better convergence speed than the other three algorithms, with a 9.9% reduction in
convergence time compared to the standard AFSA. Setting larger perception range parameter values resulted in
higher efficiency in route planning, while the step size parameter need to be adjusted according to the planning environment. The improved AFSA can provide reference for improving the efficiency of logistics UAV three-dimensional spatial route planning.

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