Dynamic path planning based on variable step size rolling window derivation and obstacle prediction

Aiming at the problem of dynamic path planning for UAVs in complex environment, a path planning algorithm combining dynamic obstacle trajectory estimation and variable step rolling window deduction is proposed. When the dynamic obstacle distance is close to the UAV, the Kalman filter is used to estimate the dynamic obstacle trajectory. Then the window deduction is performed to judge the track area of the deduction window, so that the algorithm has certain "forward-looking". In turn, the window step size, the flight speed of the drone and the flight direction are changed, and the avoidance of the dynamic obstacle is completed, and the final goal is reached by the rolling plan. The experimental analysis shows that the algorithm can complete the dynamic path planning of UAVs in complex environment in real time. (paper)