Hierarchical Planning with Annotated Skeleton Guidance

Diane Uwacu, Ananya Yammanuru, Marco Morales, Nancy M. Amato

Research output: Contribution to journalArticlepeer-review

Abstract

We present a hierarchical skeleton-guided motion planning algorithm to guide mobile robots. A good skeleton maps the connectivity of the subspace of c-space containing significant degrees of freedom and is able to guide the planner to find the desired solutions fast. However, sometimes the skeleton does not closely represent the free c-space, which often misleads current skeleton-guided planners. The hierarchical skeleton-guided planning strategy gradually relaxes its reliance on the workspace skeleton as <inline-formula><tex-math notation="LaTeX">$\mathcal {C}_{space}$</tex-math></inline-formula> is sampled, thereby incrementally returning a sub-optimal path, a feature that is not guaranteed in the standard skeleton-guided algorithm. Experimental comparisons to the standard skeleton guided planners and other lazy planning strategies show significant improvement in roadmap construction run time while maintaining path quality for multi-query problems in cluttered environments.

Original languageEnglish (US)
Pages (from-to)1-7
Number of pages7
JournalIEEE Robotics and Automation Letters
DOIs
StatePublished - Oct 1 2022
Externally publishedYes

Keywords

  • Bridges
  • Buildings
  • Costs
  • Heuristic algorithms
  • Hierarchical Motion Planning
  • Planning
  • Skeleton
  • Space exploration
  • Workspace-guided Planning

ASJC Scopus subject areas

  • Mechanical Engineering
  • Control and Optimization
  • Artificial Intelligence
  • Human-Computer Interaction
  • Control and Systems Engineering
  • Computer Vision and Pattern Recognition
  • Biomedical Engineering
  • Computer Science Applications

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