This paper presents a newly conceived planning algorithm that is based on the introduction of motion primitives in RRT*. Online computational complexity of RRT* is greatly reduced by pre-computing the optimal constrained trajectories joining pairs of starting and destination configurations in a grid space, while taking into account vehicle motion constraints in the planning task. A numerical example shows the effectiveness of the algorithm.
Using motion primitives to enforce vehicle motion constraints in sampling-based optimal planners
Sakcak, B;Bascetta, L;Ferretti, G;Prandini, M
2018-01-01
Abstract
This paper presents a newly conceived planning algorithm that is based on the introduction of motion primitives in RRT*. Online computational complexity of RRT* is greatly reduced by pre-computing the optimal constrained trajectories joining pairs of starting and destination configurations in a grid space, while taking into account vehicle motion constraints in the planning task. A numerical example shows the effectiveness of the algorithm.File in questo prodotto:
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