The comparison of four UAV path planning algorithms based on geometry search algorithm

The comparative study of four practical three-dimensional (3D) path planning algorithm based on geometry search is proceeded in this paper, the four algorithms include Dijkstra algorithm, Floyd algorithm, A∗ algorithm and Ant colony algorithm. In four algorithms, the working environments of Unmanned Aerial Vehicle (UAV) are all modeled using grid map method and UAV three-dimensional paths are all obtained by amending two-dimensional paths with the terrain following algorithm. In addition, a perpendicular approach is used to choose the key path node during UAV path planning. In this paper, online real-Time path planning abilities of the four algorithms are compared from the two aspects of the run time and the path length. Simulation results show that the four algorithms can all handle fixed threats and sudden threats, and their planning time are short; but synthetically considering the run time, complexity and path length of the four algorithms, Dijkstra algorithm is in turn better than Floyd algorithm, A∗ algorithm and Ant colony algorithm.