Leveraging Experience in Lazy Search

@article{Bhardwaj2019LeveragingEI,
  title={Leveraging Experience in Lazy Search},
  author={M. Bhardwaj and S. Choudhury and B. Boots and S. Srinivasa},
  journal={ArXiv},
  year={2019},
  volume={abs/1907.07238}
}
  • M. Bhardwaj, S. Choudhury, +1 author S. Srinivasa
  • Published 2019
  • Engineering, Computer Science
  • ArXiv
  • Lazy graph search algorithms are efficient at solving motion planning problems where edge evaluation is the computational bottleneck. These algorithms work by lazily computing the shortest potentially feasible path, evaluating edges along that path, and repeating until a feasible path is found. The order in which edges are selected is critical to minimizing the total number of edge evaluations: a good edge selector chooses edges that are not only likely to be invalid, but also eliminates future… CONTINUE READING
    Differentiable Gaussian Process Motion Planning
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