Minimizing Task-Space Frechet Error via Efficient Incremental Graph Search

Rachel Holladay, Oren Salzman, Siddhartha Srinivasa

Research output: Contribution to journalArticlepeer-review

Abstract

We present an anytime algorithm that generates a collision-free configuration-space path that closely follows a desired path in task space, according to the discrete Fréchet distance. By leveraging tools from computational geometry, we approximate the search space using a cross-product graph. We use a variant of Dijkstra's graph-search algorithm to efficiently search for and iteratively improve the solution. We compare multiple proposed densification strategies and empirically show that our algorithm outperforms a set of state-of-the-art planners on a range of manipulation problems. Finally, we offer a proof sketch of the asymptotic optimality of our algorithm.

Original languageEnglish
Article number8642910
Pages (from-to)1999-2006
Number of pages1808
JournalIEEE Robotics and Automation Letters
Volume4
Issue number2
DOIs
StatePublished - Apr 2019

Keywords

  • Motion and path planning
  • computational geometry
  • kinematics

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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