Maneuver-Based Generation of Motion Primitives for Differentially Constrained Motion Planning in State Lattices

In this paper, we propose a framework for generating motion primitives automatically. The user only needs to specify which type of maneuvers that should be included in the motion primitive set. Based on the selected maneuver types, the algorithm then solves a number of boundary value problems using numerical optimization. This significantly reduces the time consuming part of manually specifying all boundary value problems that should be solved. In addition, the framework allows for quick re-optimization of motion primitives after system parameter changes, which opens up the possibility to efficiently generate motion primitives for different types of platforms. We show in a numerical example that the framework also enhances the performance of the motion planner in terms of total cost for the produced solution.