Research Advances in Obstacle Avoidance Path Planning Algorithms for Unmanned Aerial Vehicles

With the rapid advancement of drone technology, drones have demonstrated significant application potential in various fields such as agriculture, military, and logistics due to their efficiency and flexibility. However, the practical application of drones in obstacle avoidance tasks faces multiple challenges, including complex environmental perception, algorithmic performance bottlenecks, hardware compatibility issues, and system stability and reliability. These challenges have somewhat constrained the transformation of drones' potential into actual productivity. Therefore, research and development in obstacle avoidance technology for agricultural drones are crucial. This study analyzes the current difficulties and challenges faced by obstacle avoidance path planning algorithms, focusing on the classification, principles, advantages, and disadvantages of these algorithms, as well as their optimization and application in terms of real-time performance and efficiency. The study also looks forward to the future development trends of drone obstacle avoidance path planning algorithms, suggesting that future research will concentrate on the innovative integration of multiple algorithms, deeper fusion with AI technology, optimization of algorithms for specific environments, enhancement of real-time performance and robustness, coordinated hardware development, and improvement of multi-drone collaborative algorithms. These advancements aim to adapt to more complex flying and obstacle avoidance environments, thereby promoting the standardization and industrialization of drone technology.