An overview of path planning technologies for unmanned aerial vehicles

Unmanned aerial vehicles, due to their superior maneuverability and reduced costs can easily perform tasks that are too difficult and complex to be performed with manned aircraft, under all conditions. In order to cope with various obstacles and operate in complex and unstable environmental conditions, the unmanned aerial vehicles must first plan its path. One of the most important problems to investigated in order to find an optimal path between the starting point and the target point of the unmanned aerial vehicles is path planning and choosing the appropriate algorithm. These algorithms find the optimal and shortest path, and also provide a collision-free environment for unmanned aerial vehicles. It is important to have path planning algorithms to calculate a safe path to the final destination in the shortest possible time. However, algorithms are not guaranteed to provide full performance in each path planning situation. Also, each algorithm has some specifications, these specifications make it possible to make them suitable in complex situations. Although there are many studies in path planning literature, this subject is still an active research area considering the high maneuverability of unmanned aerial vehicles. In this study, the most used methods of graph search, sampling-based algorithms and computational intelligence-based algorithms, which have become one of the important technologies for unmanned aerial vehicles and have been the subject of extensive research, are examined and their pros and cons are emphasized. In addition, studies conducted in the field of unmanned aerial vehicles with these algorithms are also briefly mentioned