An obstacle-based rapidly-exploring random tree

Samuel Rodríguez, Xinyu Tang, Jyh Ming Lien, Nancy M. Amato

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

Abstract

Tree-based path planners have been shown to be well suited to solve various high dimensional motion planning problems. Here we present a variant of the Rapidly-Exploring Random Tree (RRT) path planning algorithm that is able to explore narrow passages or difficult areas more effectively. We show that both workspace obstacle information and C-space information can be used when deciding which direction to grow. The method includes many ways to grow the tree, some taking into account the obstacles in the environment. This planner works best in difficult areas when planning for free flying rigid or articulated robots. Indeed, whereas the standard RRT can face difficulties planning in a narrow passage, the tree based planner presented here works best in these areas.

Original languageEnglish (US)
Title of host publicationProceedings 2006 IEEE International Conference on Robotics and Automation, ICRA 2006
Pages895-900
Number of pages6
DOIs
StatePublished - 2006
Externally publishedYes
Event2006 IEEE International Conference on Robotics and Automation, ICRA 2006 - Orlando, FL, United States
Duration: May 15 2006May 19 2006

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2006
ISSN (Print)1050-4729

Other

Other2006 IEEE International Conference on Robotics and Automation, ICRA 2006
Country/TerritoryUnited States
CityOrlando, FL
Period5/15/065/19/06

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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