Lattice-based planning techniques simplify the motion planning problem for autonomous vehicles by limiting available motions to a pre-computed set of primitives. These primitives are then combined online to generate more complex maneuvers. A set of motion primitives t-span a lattice if, given a real number t at least 1, any configuration in the lattice can be reached via a sequence of motion primitives whose cost is no more than a factor of t from optimal. Computing a minimal t-spanning set balances a trade-off between computed motion quality and motion planning performance. In this work, we formulate this problem for an arbitrary lattice as a mixed integer linear program. We also propose an A*-based algorithm to solve the motion planning problem using these primitives. Finally, we present an algorithm that removes the excessive oscillations from planned motions -- a common problem in lattice-based planning. Our method is validated for autonomous driving in both parking lot and highway scenarios.

翻译：基于晶格的规划技术通过将可行运动限制在预计算基元集合中，简化了自主车辆的运动规划问题。这些基元随后在线组合以生成更复杂的机动动作。给定实数t≥1时，若晶格中任何配置均可通过一系列运动基元到达，且总成本不超过最优成本的t倍，则称该基元集合构成晶格的t-跨度。计算最小t-跨度集需要在运动质量与规划性能之间权衡。本文将该问题建模为任意晶格上的混合整数线性规划，并提出了基于A*算法利用这些基元求解运动规划问题的方法。最后，我们提出一种消除规划运动中过度振荡的算法——这是基于晶格规划的常见问题。该方法在停车场与高速公路场景下的自主驾驶验证中均展现了有效性。