@inproceedings{238db4fbe0a54a5bac0395707472b76a,
title = "A geometric nonlinear observer for simultaneous localisation and mapping",
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.",
author = "Robert Mahony and Tarek Hamel",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 56th IEEE Annual Conference on Decision and Control, CDC 2017 ; Conference date: 12-12-2017 Through 15-12-2017",
year = "2017",
month = jun,
day = "28",
doi = "10.1109/CDC.2017.8264002",
language = "English",
series = "2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2408--2415",
booktitle = "2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017",
address = "United States",
}