Abstract: For real-world missions by quadrotors， complete time is an important index to measure the mission effectiveness. However， the path planning methods usually aim at the minimum path length， which can not reflect the task time accurately and directly. Thus， based on the approximate computation method of path time costs， a minimum-time obstacle-avoidance path planning algorithm is proposed for unmanned aerial vehicles. Through path tracking tests， the flight time of different maneuver styles is acquired and is used as the basis for cost calculation in the path search process. By tailoring the node expansion mode and cost-function computation method， a modified A* algorithm is proposed to achieve obstacle avoidance and path-time optimization. The simulations in radon scenarios are conducted to test the effectiveness and prior performances of the proposed method. Finally， taking substation inspection as an example， it verifies that the improved path planning method can guide the quadrotor to complete the task within a less time.

Key words: path planning, unmanned aerial vehicles, time optimal, obstacle avoidance, A* search