Robotics: Science and Systems IV

Hybrid Motion Planning Using Minkowski Sums

Jyh-Ming Lien

Abstract: Probabilistic and deterministic planners are two major approximate-based frameworks for solving motion planning problems. Both approaches have their own advantages and disadvantages. In this work, we provide an investigation to the following question: Is there a planner that can take the advantages from both probabilistic and deterministic planners? Our strategy to achieve this goal is to use the point-based Minkowski sum of the robot and the obstacles in workspace. Our experimental results show that our new method, called M-sum planner, which uses the geometric properties of Minkowski sum to solve motion planning problems, provides advantages over probabilistic or deterministic planners. In particular, M-sum planner is significantly more efficient than the Probabilistic Roadmap Methods (PRMs) and its variants in all the examples studied in this paper.



    AUTHOR    = {Jyh-Ming Lien},
    TITLE     = {Hybrid Motion Planning Using Minkowski Sums},
    BOOKTITLE = {Proceedings of Robotics: Science and Systems IV},
    YEAR      = {2008},
    ADDRESS   = {Zurich, Switzerland},
    MONTH     = {June},
    DOI       = {10.15607/RSS.2008.IV.013}