Comparative Analysis of Algorithms and Applications in Unmanned Aerial Vehicle Path Planning in Recent Years

Abstract

The research of UAVs(Unmanned Aerial Vehicle) has received a lot of attention in recent years, and more and more UAV manufacturers have emerged in China and abroad, such as DJI, 3D Robotics, Parrot and so on.The advantage of UAVs over manned vehicles is that they can perform missions in dangerous and complex environments, such as fires, battlefields, earthquake debris, etc.With the increase in automation and intelligence of UAVs, UAV technology has been developed as never before, and it will play an increasingly important role in the future military and civilian sectors.On the military side, UAVs can perform military tasks such as reconnaissance, attack, and electronic countermeasures.On the civilian side, UAVs can be used for weather detection, pesticide spraying, geological surveys, disaster relief and many other areas.The path planning system plays a crucial role when UAVs perform these tasks.Due to the fuel limitation of UAVs, how to avoid obstacles and choose the proper route in a reasonable and safe manner, and even how to deal with unexpected situations, become the focus of UAV path planning.In recent years, many new path planning algorithms have been proposed to accomplish these increasingly complex tasks.Then, the advantages and disadvantages of GA(Genetic Algorithm), ACO(Ant Colony Optimization), and PSO(Particle Swarm Optimization)are discussed, and the future development direction and trend of UAV path planning is outlined.