Rapidly-exploring random tree based memory efficient motion planning

Olzhas Adiyatov, Huseyin Atakan Varol

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

52 Citations (Scopus)

Abstract

This paper presents a modified version of the RRT* motion planning algorithm, which limits the memory required for storing the tree. We run the RRT* algorithm until the tree has grown to a predefined number of nodes and afterwards we remove a weak node whenever a high performance node is added. A simple two-dimensional navigation problem is used to show the operation of the algorithm. The algorithm was also applied to a high-dimensional redundant robot manipulation problem to show the efficacy. The results show that our algorithm outperforms RRT and comes close to RRT* with respect to the optimality of returned path, while needing much less number of nodes stored in the tree.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2013
Pages354-359
Number of pages6
DOIs
Publication statusPublished - Nov 25 2013
Event2013 10th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2013 - Takamastu, Japan
Duration: Aug 4 2013Aug 7 2013

Publication series

Name2013 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2013

Other

Other2013 10th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2013
CountryJapan
CityTakamastu
Period8/4/138/7/13

Keywords

  • Motion Planning
  • Path Planning
  • Rapidly-Exploring Random Trees
  • Redundant Manipulators

ASJC Scopus subject areas

  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Mechanical Engineering

Fingerprint Dive into the research topics of 'Rapidly-exploring random tree based memory efficient motion planning'. Together they form a unique fingerprint.

Cite this