UAV route planning based on the Improved Genetic Algorithm
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Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

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TP18

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    Abstract:

    Aiming at the shortest optimal route planning, firstly, this paper comprehensively analyzes the constraints and simulation environment of UAV route planning, constructs the route planning algorithm simulation environment, defines the performance constraints of UAV, and then proposes a route evaluation function that can integrate multiple constraints; Then, aiming at the problems of local optimum and slow convergence of genetic algorithm, considering the coupling relationship between the problems, a fusion improvement scheme of fitness value calibration, population diversification and elite retention strategy is proposed. The experimental results show that the improved genetic algorithm can save about 11.8% fuel loss, and the UAV has relatively fewer maneuvers, which improves the flight safety and efficiency of UAV.

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History
  • Received:
  • Revised:
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  • Online: July 02,2024
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