Spatio-Temporal Lattice Planning Using Optimal Motion Primitives

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.