Sparse Multilevel Roadmaps for High-Dimensional Robotic Motion Planning
Andreas Orthey,Marc Toussaint,Andreas Orthey,Marc Toussaint
Sparse roadmaps are important to compactly represent state spaces, to determine problems to be infeasible and to terminate in finite time. However, sparse roadmaps do not scale well to high-dimensional planning problems. In prior work, we showed improved planning performance on high-dimensional planning problems by using multilevel abstractions to simplify state spaces. In this work, we generalize...
