Multi-UAV path planning based on an improved wolf pack algorithm in complex 3D terrains

With the diversification of mission attributes and the complexity of mission environments, multi-UAV collaboration has emerged as an effective approach to address complex missions and environments by compensating for the limitations of a single UAV. Among these challenges, multi-UAV path planning is a critical issue that must be resolved to accomplish specific flight missions in complex environments. To this end, this paper proposes a multi-UAV path planning scheme based on an improved Wolf Pack Algorithm (WPA) for complex Three-Dimensional (3D) terrains. Specifically, the chaotic sequence is employed to optimize the initial distribution of wolf pack, while the variable-direction walking strategy and adaptive step-size mechanism are introduced to enhance the randomness of wolf pack search. Furthermore, a Hamming distance based similarity judgment mechanism is leveraged to update the wolf pack and maintain the continuous evolution of the population. Finally, the improved WPA is applied to the multi-UAV 3D path planning, where multiple UAVs plan safe paths from their respective starting positions to target locations based on real-time environmental information and constraint conditions. Simulation results demonstrate that the proposed path planning scheme can not only adapt well to complex 3D terrains but also plan the optimal flight path.