Abstract
In the complex environment, using traditional pigeon-inspired optimization algorithm for the UAV route planning leads local optimum and slow convergence speed and unstable problem. In order to solve this problem, this paper introduces an adaptive weighted pigeon-inspired optimization algorithm. The adaptive weight coefficient is applied to calculate the speed and position of the individuals in the population which enhances the quality and efficiency of route planning. In addition, this paper done many simulation experiment from different aspect for providing enough evident in path planning. This paper also have these simulation experiment by designing different environment model including the simple and complex environment. The simulation results show that the adaptive weighted pigeon-inspired optimization algorithm provides a shorter route distance, a lower threat cost consumption and the algorithm running time while comparing with pigeon-inspired optimization algorithm and particle swarm optimization than basic pigeon-inspired optimization algorithm and Particle swarm intelligence algorithm. After the spline smoothing, the UAV route is flyable.
Published Version
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