Path planning with static obstacles for USVs via the Hybrid A* algorithm and the artificial potential field method

This paper considers the problem of excessive iterations and unnecessary steering actions for unmanned surface vehicles (USVs) by a path planning method combining the Hybrid A* algorithm and the APF method. First, the proposed path planning method is used to generate the collsion-free global path as the reference line in the Frenet coordinate system. Through decoupling the motions into the longitudinal and horizontal motion, the optional trajectory sets of USVs are selected based on the relative position to the reference line. According to the cost function within the lateral and longitudinal orientations, the minimum-cost path can be calculated. In addition, the jerk optimization is adopted to smooth the path. Finally, three numerical examples, including two kinds of extra penalties, are given to illustrate the effectiveness of path planning for USVs on a grid map with static obstacles.