Hierarchical Planning with Annotated Skeleton Guidance

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

Research output: Contribution to journalArticlepeer-review


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 C 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)11055-11061
Number of pages7
JournalIEEE Robotics and Automation Letters
Issue number4
StatePublished - Oct 1 2022


  • Motion planning
  • path planning
  • semantic scene understanding

ASJC Scopus subject areas

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


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