Path Planning Method for UAV in Complex Mountainous Areas Based on Meta-heuristic Algorithms

In recent years, drone technology has been rapidly advancing, and its application areas are continuously expanding. In disaster response and search and rescue operations, drones can access areas that are difficult or unsafe for humans to reach. Path planning for drones in complex mountainous environments has always been a crucial component of drone technology. Metaheuristic algorithms, compared to traditional algorithms, exhibit excellent flexibility and diversity in this field, and have become an effective means of solving complex multi-constraint combinatorial optimization problems due to their speed and efficiency. This paper conducts comparative experimental tests on the latest eight metaheuristic drone path planning algorithms, verifying their effectiveness in complex environments and revealing the characteristics and advantages of each algorithm. RBMO demonstrates the most superior performance and stability in complex mountainous environments. On the other hand, the SSA algorithm exhibits the fastest convergence speed. This paper provides a theoretical reference for research on drone path planning problems.