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 language | English |
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Article number | 8642910 |
Pages (from-to) | 1999-2006 |
Number of pages | 1808 |
Journal | IEEE Robotics and Automation Letters |
Volume | 4 |
Issue number | 2 |
DOIs | |
State | Published - 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