Aiming at the dynamic track planning problem of multi-rotor unmanned aerial vehicle (UAV) in complex environment space, this paper proposes a "high-dimensionality-reduced space environment modelling method", in this way, the complexity of environment model will be reduced and the planning efficiency will be improved. In addition, the paper proposes an improved artificial potential field (APF) method. First obtain overall environmental information through the A∗ algorithm, and optimise the global path nodes. Then improve the potential function of the APF method, and add the attraction of the global path to the UAV, so that it can guide the UAV movement smoothly. By analysing the simulation results, it can be found that this method can make up for the shortcomings of APF method in path guidance to a certain extent. The effective combination of the two algorithms improves the UAV's path planning ability in complex environments.