Three-dimensional path planning of unmanned aerial vehicle under complicated environment

Simulation of unmanned aerial vehicle (UAV) flight environment is one of the key technologies in three-dimensional path planning. We adopt efficient intelligent algorithm for path planning in the simulation environment. Basic ant colony algorithm is easy to reach local optimum prematurely with slow convergence speed and long computing time. In this paper, information of the shortest distance is sent to the system for controlling, and optimize the node selection method by improving the calculation of state transition probability. In addition, the local updating rules are improved in order to improve the efficiency of the algorithm. The simulation results show that the improved ant colony algorithm is used to meet the requirements of the unmanned aerial vehicle flight track.