Obstacle Avoidance Strategy for Quadrotor UAV based on Improved Particle Swarm optimization Algorithm

Rotor unmanned aerial vehicles (UAVs) have been widely used in daily life due to their high flexibility and controllability. To ensure the flight safety of UAVs, this paper proposes a new obstacle avoidance strategy. First, the laser sensor TFmini is used to detect distances and orientations of the obstacles near a quadrotor UAV. Second, after modeling the flight environment, the Dijkstra method is employed to search the feasible paths for the UAV. Third, the particle swarm optimization algorithm (PSO) is presented to obtain a global optimal path, based on the standard PSO algorithm, an improved version is proposed to search a better solution. Simulation results demonstrate that the proposed obstacle avoidance strategy of UAVs can obtain an ideal global optimal path.