Multilevel Motion Planning
Project Goal
Develop algorithms which can plan robot motions over multiple levels of abstraction while keeping formal guarantees like probabilistic completeness and asymptotic optimality.
Code
An existing implementation of the quotient space planning framework is available in the Open Motion Planning Library (OMPL). Check out the overview and the tutorial.
Contributors
Andreas Orthey, Marc Toussaint, Sohaib Akbar, Adrien Escande, Eiichi Yoshida
Publications
Andreas Orthey, Sohaib Akbar, Marc Toussaint, Multilevel Motion Planning: A Fiber Bundle Formulation, arXiv:2007.09435 [cs.RO], 2020, [PDF-preprint] [Bibtex]
Andreas Orthey, Marc Toussaint, Section Patterns: Efficiently Solving Narrow Passage Problems in Multilevel Motion Planning, IEEE Transactions on Robotics, 2021, [PDF] [Bibtex]
Andreas Orthey, Marc Toussaint, Sparse Multilevel Roadmaps for High-Dimensional Robotic Motion Planning, IEEE International Conference on Robotics and Automation (ICRA), 2021, [PDF] [BlogPost] [Bibtex]
Andreas Orthey, Marc Toussaint, Rapidly-Exploring Quotient-Space Trees: Motion Planning using Sequential Simplifications, International Symposium on Robotics Research (ISRR), 2019, [PDF] [Bibtex]
Andreas Orthey, Adrien Escande, Eiichi Yoshida, Quotient-Space Motion Planning, IEEE International Conference on Intelligent Robots and Systems (IROS), 2018, [PDF] [Bibtex]
#MultilevelMotionPlanning #QuotientSpacePlanning #SparseMultilevelRoadmaps