Abstract
Aiming at the problem of unmanned aerial vehicle’s(UAV) path planning in complex battlefield environment, this paper proposes an improved grey wolf optimization algorithm (IGWO). UAV path planning is to plan the flight path from the starting point to the target point under the conditions of ensuring the best performance and satisfying different constraints. Based on the traditional GWO algorithm, this paper proposes two improvements: adjusting the decay form of the convergence factor, and re-updating the location according to weighted sum of ϕ, φ, χ. Furthermore, under the consideration of various constraints, a 3D path planning strategy for UAV based on IGWO is constructed to obtain the UAV path with the optimal comprehensive performance. Finally, the comparative simulations with three other algorithms are carried out. The simulation result shows that IGWO can be implemented for achieving optimal UAV path planning, and IGWO outperforms the other three optimization algorithms.
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