In this paper, we propose a curvature path planning algorithm for unmanned surface vehicles (USVs). To control the USV automatically, various robot navigation techniques can be applied and numerous researchers are working on a grid map-based path planning algorithms. However, the most grid map-based path planning methods for the USVs consider only two-dimensional (
) plane without considering vehicle’s maximum curvature. Since the most of the USVs are typically highly under-actuated, the ship tends to result in failure and sometimes induces hazardous collision situation when the ship follows the resultant path generated by the two-dimensional path planning algorithm. To solve this problem, we construct a non-uniform grid map which can reflect the geometric cost. Next we extend the dimension to reflect the kinematic constraint of the USV. Finally, to consider the vehicle’s dynamic constraint, we propose a new cost function. The result of the proposed algorithm has been demonstrated through the simulation on the real map and the results show that the proposed algorithm generates the most plausible and efficient path.