Robust adaptive motion planning in the presence of dynamic obstacles

Nurali Virani, Minghui Zhu

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    Usually in game theoretic formulations for robust motion planning, the model as well as the capabilities (input set) of all dynamic obstacles are assumed to be known. This paper aims to relax the assumption of known input set by proposing a unified framework for motion planning and admissible input set estimation. The proposed approach models every dynamic obstacle as an uncertain-constrained system and then uses the uncertainty estimation technique to estimate the bounds of those uncertainties. The RRT∗ algorithm with uncertainty estimation for robust adaptive motion planning in presence of dynamic obstacles is presented in this paper. Simulation examples have been used to validate the proposed algorithm.

    Original languageEnglish (US)
    Title of host publication2016 American Control Conference, ACC 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages2104-2109
    Number of pages6
    ISBN (Electronic)9781467386821
    DOIs
    StatePublished - Jul 28 2016
    Event2016 American Control Conference, ACC 2016 - Boston, United States
    Duration: Jul 6 2016Jul 8 2016

    Publication series

    NameProceedings of the American Control Conference
    Volume2016-July
    ISSN (Print)0743-1619

    Other

    Other2016 American Control Conference, ACC 2016
    CountryUnited States
    CityBoston
    Period7/6/167/8/16

    Fingerprint

    Motion planning
    Dynamic models
    Uncertainty

    All Science Journal Classification (ASJC) codes

    • Electrical and Electronic Engineering

    Cite this

    Virani, N., & Zhu, M. (2016). Robust adaptive motion planning in the presence of dynamic obstacles. In 2016 American Control Conference, ACC 2016 (pp. 2104-2109). [7525229] (Proceedings of the American Control Conference; Vol. 2016-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2016.7525229
    Virani, Nurali ; Zhu, Minghui. / Robust adaptive motion planning in the presence of dynamic obstacles. 2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 2104-2109 (Proceedings of the American Control Conference).
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    abstract = "Usually in game theoretic formulations for robust motion planning, the model as well as the capabilities (input set) of all dynamic obstacles are assumed to be known. This paper aims to relax the assumption of known input set by proposing a unified framework for motion planning and admissible input set estimation. The proposed approach models every dynamic obstacle as an uncertain-constrained system and then uses the uncertainty estimation technique to estimate the bounds of those uncertainties. The RRT∗ algorithm with uncertainty estimation for robust adaptive motion planning in presence of dynamic obstacles is presented in this paper. Simulation examples have been used to validate the proposed algorithm.",
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    Virani, N & Zhu, M 2016, Robust adaptive motion planning in the presence of dynamic obstacles. in 2016 American Control Conference, ACC 2016., 7525229, Proceedings of the American Control Conference, vol. 2016-July, Institute of Electrical and Electronics Engineers Inc., pp. 2104-2109, 2016 American Control Conference, ACC 2016, Boston, United States, 7/6/16. https://doi.org/10.1109/ACC.2016.7525229

    Robust adaptive motion planning in the presence of dynamic obstacles. / Virani, Nurali; Zhu, Minghui.

    2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 2104-2109 7525229 (Proceedings of the American Control Conference; Vol. 2016-July).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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    AB - Usually in game theoretic formulations for robust motion planning, the model as well as the capabilities (input set) of all dynamic obstacles are assumed to be known. This paper aims to relax the assumption of known input set by proposing a unified framework for motion planning and admissible input set estimation. The proposed approach models every dynamic obstacle as an uncertain-constrained system and then uses the uncertainty estimation technique to estimate the bounds of those uncertainties. The RRT∗ algorithm with uncertainty estimation for robust adaptive motion planning in presence of dynamic obstacles is presented in this paper. Simulation examples have been used to validate the proposed algorithm.

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    Virani N, Zhu M. Robust adaptive motion planning in the presence of dynamic obstacles. In 2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 2104-2109. 7525229. (Proceedings of the American Control Conference). https://doi.org/10.1109/ACC.2016.7525229