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Estimation, Search, and Planning (ESP) Research Group

Informed RRT*

Source Code

Informed RRT* is now part of the Open Motion Planning Library (OMPL). You can find details on how to download and install OMPL on their website.

Description

Informed RRT* is an improvement to the RRT* algorithm that increases the rate at which the found solution converges to the optimum. Developed specifically for problems seeking to minimize path-length, this work uses a method to directly sample the subset of a planning problem that contains all possible improvements to a given solution. In doing so, it continues to consider all relevant paths without requiring any additional parameters.

This direct informed sampling is actually required to generally solve the planning problem, as the probability of improving a given solution goes to zero as the size of the problem domain, or the number of dimensions, increases. For a 6DOF arm, even an intelligent sample-rejection technique will limit the probability of improvement at each iteration to ~8%, while direct sampling imposes no such limit.

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  1. Authors
    1. J. D. Gammell
    2. T. D. Barfoot
    3. S. S. Srinivasa
    Title
    Informed sampling for asymptotically optimal path planning
    Publication
    Journal
    IEEE Transactions on Robotics (T-RO)
    Volume
    34
    Number
    4
    Pages
    966–984
    Date
    Code
    Code
    Digital Object Identifier (DOI)
    doi: 10.1109/TRO.2018.2830331
    Google Scholar
    Google Scholar
  2. Award
    Author
    J. D. Gammell
    Title
    Informed anytime search for continuous planning problems
    Publication
    Type
    Ph.D. Thesis
    School
    University of Toronto
    Date
    Digital Object Identifier (DOI)
    doi: 1807/78630
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    Google Scholar
  3. Authors
    1. J. D. Gammell
    2. S. S. Srinivasa
    3. T. D. Barfoot
    Title
    Informed RRT*: Optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic
    Publication
    Conference
    Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
    Pages
    2997–3004
    Location
    Chicago, IL, USA
    Date
    Code
    Code
    Videos
    Video
    Presentations
    Presentation
    PDFs
    PDF
    Digital Object Identifier (DOI)
    doi: 10.1109/IROS.2014.6942976
    Google Scholar
    Google Scholar