A geometric nonlinear observer for simultaneous localisation and mapping

Robert Mahony, Tarek Hamel

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    32 Citations (Scopus)

    Abstract

    The Simultaneous Localisation and Mapping (SLAM) problem involves estimating the pose of a robot relative to landmarks observed in the environment while at the same time estimating the location of those landmarks in the environment. This paper introduces a framework in which the landmarks and robot pose can be modelled in a single geometric structure, that of a homogeneous space obtained as the quotient of a novel Lie-group that we term the SLAMn(3) group. Using this formulation we apply techniques from observer design for symmetric systems to derive a novel observer for the SLAM problem posed in continuous-time.

    Original languageEnglish
    Title of host publication2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages2408-2415
    Number of pages8
    ISBN (Electronic)9781509028733
    DOIs
    Publication statusPublished - 28 Jun 2017
    Event56th IEEE Annual Conference on Decision and Control, CDC 2017 - Melbourne, Australia
    Duration: 12 Dec 201715 Dec 2017

    Publication series

    Name2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
    Volume2018-January

    Conference

    Conference56th IEEE Annual Conference on Decision and Control, CDC 2017
    Country/TerritoryAustralia
    CityMelbourne
    Period12/12/1715/12/17

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