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Spatio-Temporal Lattice Planning Using Optimal Motion Primitives
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AI
DOI：10.1109/TITS.2023.3297068.png)
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Abstract
En 中文
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 >= 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.
Keywords:
Motion planning
autonomous driving
trajectory optimization
path planning
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