Flight Path Planning for UAVs in Environment with Moving Obstacles

Pre flight planning is essential for any aircraft, especially Unmanned Aerial Vehicles (UAVs), as it forms the foundation for successful mission execution. This process is inherently complex, requiring a detailed assessment of dynamic factors that may impact mission success, including both static and moving obstacles. In this paper, we propose a novel path-planning approach that extends beyond traditional algorithms like Rapidly-exploring Random Tree (RRT). Our method inte-grates real time responsiveness to account for moving obstacles, enhancing the efficiency, speed, and adaptability of UAV path finding in unpredictable environments. This approach aims to improve UAV safety, increase mission reliability, and provide a robust framework for autonomous UAV operations in complex, real world scenarios.