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

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