In view of the shortcomings of traditional Ant Colony Optimization (ACO) algorithm in path planning of Unmanned Aerial Vehicle (UAV)such as slow convergence speed and easy to fall into local optimal solutionan Improved Adaptive Ant Colony Optimization (IAACO) algorithm is proposed.Firstlyin order to make ants move in the direction of the target point with greater probability and improve the search efficiency of the pathan angle guidance factor is introduced into the transfer probability of ACO.Thenheuristic information adaptive adjustment factor is introduced to balance the convergence and global search ability of the algorithm.Finallyby defining length index function and angle index functionthe objective function of route optimization is further established,and the global optimization of UAV route planning is realized.Experimental results show that the improved algorithm converges fasterand the generated track is smoother and shorter.