Informed RRT∗ towards optimality by reducing size of hyperellipsoid

Min Cheol Kim, Jae Bok Song

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Citations (Scopus)

Abstract

Wrapping-based informed RRT∗ is a modified version of informed RRT∗. Informed RRT∗ formulates an n-dimensional hyperellipsoid from which it generates new sample nodes. This has a dramatically increased chance of sampling nodes that will improve the current best solution compared to conventional RRT∗. However, due to explorative and randomized behaviors of RRT∗, the size of the hyperellipsoid will unlikely be small enough to call it effective. To solve this matter, wrapping-based informed RRT∗ proposed in this paper combines a size-diminishing procedure called 'wrapping process' with informed RRT∗. The proposed planner can advance from the first solution acquired by the planner to the improved, feasible solution which can drastically reduce the size of the hyperellipsoid. Therefore, the required time consumption in order to acquire the globally optimal solution is reduced dramatically. The algorithm was tested in various environments with different numbers of joint variables and showed much better performance than the existing planners. Furthermore, the wrapping process proved to be a comparably insignificant computational burden regardless of the number of dimensions of the configuration space.

Original languageEnglish
Title of host publicationAIM 2015 - 2015 IEEE/ASME International Conference on Advanced Intelligent Mechatronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages244-248
Number of pages5
ISBN (Electronic)9781467391078
DOIs
Publication statusPublished - 2015 Aug 25
EventIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2015 - Busan, Korea, Republic of
Duration: 2015 Jul 72015 Jul 11

Publication series

NameIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
Volume2015-August

Other

OtherIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2015
Country/TerritoryKorea, Republic of
CityBusan
Period15/7/715/7/11

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

  • RRT
  • RRT
  • Sampling-based motion planning
  • optimal motion planning

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Science Applications
  • Electrical and Electronic Engineering

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