Multi-UAV Path Planning using Grey Wolf Optimization and RRT Algorithm

This paper presents a multi-UAV path planning approach using the Grey Wolf Optimization (GWO) algorithm and the Rapidly-exploring Random Tree (RRT) algorithm. The proposed method aims to optimize UAV paths cooperatively, considering constraints such as threat zones, altitude limits, and synchronization requirements. The performance of the combined approach is evaluated through comprehensive simulations, demonstrating its effectiveness in generating efficient and collision-free paths for multiple UAVs. The integration of GWO and RRT leverages the strengths of both algorithms, providing a robust solution for complex path planning scenarios. This approach enhances the efficiency and robustness of multi-UAV path planning, making it suitable for real-world applications where UAVs must navigate complex environments with dynamic constraints. The future version is expected to include more functionality, including encryption capabilities and analytics for enhanced security and analytical capacity.