Autonomous navigation of ships by combining optimal trajectory planning with informed graph search

Abstract

Autonomous trajectory generation plays an essential role in the navigation of vehicles in space as well as in terrestrial scenarios, i.e. in the air, on solid ground, or water. For the latter, the navigation of ships in ports has specific challenges since ship dynamics are highly nonlinear with limited agility, while the manoeuvre space in ports is limited. Nevertheless, for providing support to humanly designed control strategies, autonomously generated trajectories have not only to be feasible, i.e. collision-free but shall also be optimal with respect to manoeuvre time and control effort. This article presents a novel approach to autonomous trajectory planning on the basis of precomputed and connectable trajectory segments, the so-called motion primitives, and an A*-search algorithm. Sequences of motion primitives provide an initial guess for a subsequent optimization by which optimal trajectories are found even in terrains with many obstacles. We illustrate the approach with different navigation scenarios.