Improving Autonomus Drone Navigation using a Star Pathing Algorithm

Drone navigation in complex and dynamic environments is a significant challenge in robotics. This paper investigates the application of the A* (A star) graph pathfinding algorithm for efficient and reliable unmanned aerial vehicle (>UAV) navigation. By leveraging the heuristic-based nature of A*, drones can identify optimal paths while minimizing computational overhead. This study benchmarks the A* algorithm against other pathfinding techniques in both simulated and real-world scenarios, demonstrating its effectiveness in enhancing route planning, obstacle avoidance, and energy efficiency. Additionally, a detailed literature review highlights the evolution of pathfinding techniques and their applicability to UAV navigation.