In air-ground collaborative operation scenarios,UAVs are required to have the capabilities of rapid path planning and accurate autonomous landing at the same time,which poses higher requirements on the real-time performance and accuracy of the algorithm under limited computing resources of the UAVs.This paper mainly solves the key technological problem of integrated realization of UAV rapid path planning and autonomous landing function.Firstly,to solve the problems of the traditional A* algorithm of bad real-time performance and abundant resource consumption,the traditional eight-neighborhood search approach is expanded to the sixteen-direction search approach,a high-matching-degree heuristic function is designed,and an adaptive weight coefficient is introduced to comprehensively enhance the performance of the path planning algorithm.Secondly,oriented to the scenario of air-ground collaborative operations,a UAV autonomous landing strategy based on visual feedback is designed,which improves the accuracy of autonomous landing.Finally,simulation and experiments are performed to verify the performance of the proposed enhanced A* algorithm,autonomous landing and the integrated realization strategy.The results show that the enhanced A* algorithm shortens the length of the planned path and improves the smoothness of the planned path,and the real-time performance of the algorithm is improved to a great extent,which meets the requirements of real-time obstacle avoidance and path planning in complex environments.Meanwhile,the UAV can quickly and steadily land at the target point on the ground platform.