Spatio-Temporal Lattice Planning Using Optimal Motion Primitives
Alexander Botros, STEPHEN L. J. SMITH · IEEE Transactions on Intelligent Transportation Systems · 2023
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 combined online to generate complex maneuvers. A set of motion primitives$t$-span a lattice if, given a real number$t\geq 1$, 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 and 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.