Aiming at the problems of low efficiency and lack of practicality of path planning for quadcopter UAV in indoor environments,a path planning method based on the fusion improvement algorithm is proposed.Firstly,indoor mixing constraints are introduced and dynamic weighting is used to reconstruct the evaluation function of the traditional A* algorithm.Secondly,the neighborhood search method is adaptively adjusted according to the azimuthal angle of different map areas;then the safety radius is set considering the influence of the actual size of the UAV and the path is redundantly processed at the inflection points using Floyd's algorithm.Finally,indoor autonomous path planning and obstacle avoidance are realized by integrating the improved A"algorithm and the improved DWA algorithm.The results in different simulation environments of MATLAB show that the number of search nodes and the turning angle of the improved algorithm are reduced by an average of 63.1%and 58.9%,respectively,which ensures the optimization of the global path and improves the searching efficiency and the path safety at the same time.As verified by the experimental results of ROS operating system,the fusion algorithm has obvious advantages in obstacle avoidance effect and smoothness of movement,and can be applied to the path planning of UAVs in indoor complex scenes.