Abstract:

In view of the local minimum value, unreachable target and path oscillation in the practical application of traditional artificial potential field method, this study proposes an improved artificial potential field method based on deflection angle suppression. Based on the traditional artificial potential field method, this method adopts the improved repulsive potential field function to ensure that the target point is the lowest point of the whole situation. The deflection angle inhibitor is introduced in the path solution to suppress the excessive deflection angle during the driving process of the unmanned vehicle. After the unmanned vehicle falls into the local minimum point, a new virtual target point is added to the path solution at each step until the unmanned vehicle accumulates a certain deflection angle to get rid of the obstacle group. The simulation results show that the algorithm can reduce the volatility of the planning path without affecting the obstacle avoidance of the unmanned vehicle, and enable the unmanned vehicle to smoothly escape the complex obstacle group, smoothly reach the target point, and plan an effective, short and less oscillating path.

Key words: artificial potential field method, path planning, driverless vehicle, oscillation filtering, deflection angle suppression, virtual target point, local minimum, obstacle avoidance