Path Planning of Multirotor UAV Based on the Improved Ant Colony Algorithm

Path planning is an important part of the unmanned aerial vehicle (UAV) to realize its autonomous capabilities. Aiming at shortcomings traditional ant colony algorithm-based trajectory method, which has slow convergence speed and easy fall into local optimum, a path method based on improved algorithm proposed. First, dynamic adjusting factor added heuristic function improve directivity selection search speed. Then, state transition strategy solve problem in initial stage optimum later stage. Finally, inflection point smoothly optimized through cubic B-spline curve. Simulation results show that can quickly converge optimal well adapt flight requirements multirotor UAV.