The landing obstacle avoidance control of quadcopter unmanned aerial vehicles in complex environments involves dual challenges of obstacle avoidance and precise landing. To solve the problems of low efficiency and easy to fall into local optima in landing obstacle avoidance trajectory planning, a PID control method for quadcopter unmanned multi aircraft landing obstacle avoidance trajectory is proposed. Using grid method to build a flying environment, constructing obstacle repulsion field based on potential field method, combining ant colony algorithm with potential field method, setting ant individuals as aircraft, and selecting forward grid points based on pheromone concentration, gravity field, and repulsion field values. After the aircraft arrives at the landing site, the trajectory optimization is updated and diffused. After reaching the maximum round, the highest optimization trajectory is smoothed using B-spline curves to obtain the final landing obstacle avoidance trajectory. This solves the safety, efficiency, and adaptability problems of trajectory planning in complex environments. By integrating potential fields with ant colony algorithms, trajectory planning becomes more intelligent. In terms of aircraft control, PID control is used as technical support. The throttle controller adopts PD control, and the attitude controller adopts cascade PID control, respectively controlling the angular velocity and angle of the attitude. The horizontal position controller adopts PID control, which calculates the deviation between the current position of the aircraft and the corresponding position of the trajectory, obtains the pitch angle and roll angle, and then achieves horizontal position control. The test results show that the proposed method can enable quadcopter unmanned aerial vehicles to successfully avoid obstacles with a small deviation of less than 2cm, and land accurately with a deviation approaching 0cm, which has high practical value.