Underactuated surface vessel path planning and following control based on an improved artificial potential field method

Abstract

To study the problem of ensuring that an underactuated surface vessel can arrive at its destination automatically, accurately, and safely from its starting position according to a pre-planned route, this paper presents a ship path planning and following control method based on improved artificial potential field method. The simulated annealing algorithm is used to optimize the repulsion function of the traditional artificial potential field method, which effectively solves the defects of the traditional artificial potential field method, such as unreachable target and the tendency to easily fall into local minimum value. The planned optimal path is taken as the expected input of the ship motion control system, and the control rate of ship kinematics tracking is designed based on the idea of inner and outer loop control, which are widely used in the industry. This approach better solves the problem of underactuated surface vessel path following. In a ship dynamic subsystem, with the use of the unmodeled dynamics and external disturbances of neural network approximation dynamic subsystem, the designed synovial tracking controller of the neural network can effectively track the boot rate signal of the kinematics subsystem and, at the same time, solve the traditional artificial potential field method for path planning without overall consideration of the defects of navigable environment disturbance. Simulation experiments verify the effectiveness of ship path planning and tracking control based on an improved artificial potential field algorithm.