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Adaptive multi-UAV path planning method based on improved gray wolf algorithm
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AI
DOI：10.1016/j.compeleceng.2022.108377.png)
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Abstract
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Due to the slow convergence and insufficient flight path in path planning, we proposes an adaptive multi-UAV path planning method (AP-GWO) that improves the gray wolf algorithm. The spiral update position method is introduced using the whale algorithm as reference, while the probability of selecting the update method is set to the golden ratio of 0.618. Afterwards, in the iterative process, a different number of leadership levels is used to update the position of the individual, and the leadership is adjusted using an adaptive mechanism. The number of strata balances the process of encirclement and attack. The experimental results show that the proposed AP-GWO method can shorten the flight time of the UAV by an average of 22.8%, shorten the convergence time of the algorithm, and make the flight path of the UAV smoother.
Keywords:
Gray wolf algorithm
Path planning
Adaptive
Convergence time
Smoothness
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C
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4.9
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6.7K
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1.3W
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