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.

摘要

自主轨迹生成在空间和陆地场景（即空中、固体地面或水中）的车辆导航中起着至关重要的作用。对于后者，船舶在港口的航行具有特定的挑战，因为船舶动力学是高度非线性的，灵活性有限，而港口的机动空间有限。然而，为了支持人工设计的控制策略，自主生成的轨迹不仅要可行，即无碰撞，而且在机动时间和控制努力方面也应该是最佳的。本文提出了一种基于预先计算和可连接的轨迹段、所谓的运动原语和 A* 搜索算法的自主轨迹规划的新方法。运动图元序列为后续优化提供了初始猜测，即使在具有许多障碍物的地形中也可以找到最佳轨迹。我们用不同的导航场景来说明该方法。