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Estimation, Search, and Planning (ESP) Research Group

Task and Motion Informed Trees (TMIT*)

Source Code

A public implementation of TMIT* will be available in this GitHub repository very soon.

Description

Task and Motion Informed Trees (TMIT*) is a practical approach to almost-surely asymptotically optimal integrated task and motion planning (TMP). It uses relaxed symbolic planning and anytime satisfaction of action preconditions to efficiently discover candidate symbolic plans. It then uses AIT* to lazily validate these symbolic plans and find and improve compatible motion plans. This hierarchical, interleaved approach allows TMIT* to share information between all aspects of the TMP search and delay computationally expensive operations until necessary. As a result, TMIT* finds initial solutions quickly and converges toward the optimal integrated task and motion plan in an anytime manner.

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  1. Authors
    1. W. Thomason
    2. M. P. Strub
    3. J. D. Gammell
    Title
    Task and Motion Informed Trees (TMIT*): Almost-surely asymptotically optimal integrated task and motion planning
    Publication
    Journal
    IEEE Robotics and Automation Letters (RA-L)
    Volume
    7
    Number
    4
    Pages
    11370–11377
    Date
    Notes
    To be presented at IROS 2022
    Code
    Code
    Digital Object Identifier (DOI)
    doi: 10.1109/LRA.2022.3199676
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