Aiming at the path planning problem of logistics unmanned aerial vehicles (UAVs) that can deliver multiple packages, this paper comprehensively considers the maximum travel distance of UAVs, the maximum carrying capacity, the geographical location of delivery centers and delivery points, and the priority of packages, with the shortest flight distance and the highest customer satisfaction as the objectives. A multi-objective programming model with multiple constraints is constructed and an improved simulated annealing algorithm is designed. By constructing a specific solution space and calculating the probability of accepting new solutions, the global optimal solution can be obtained by avoiding local optima as much as possible. Finally, the sensitivity of initial temperature, temperature gradient, and iteration times of simulated annealing is analyzed. The results show that the simulated annealing algorithm can efficiently plan the UAV navigation path and minimize the cost. When the initial temperature is 180℃~ 220℃, the temperature gradient is 4℃, and the number of iterations is between 200 and 300, the probability of obtaining the global optimal solution is the highest. The research results can provide guidance and reference value for the application of UAVs in logistics distribution systems.
Path planning of multi-parcel UAV based on improved simulated annealing algorithm
International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021) ; 2021 ; Nanchang,China
Proc. SPIE ; 12172
04.05.2022
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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