Guaranteed Performance Nonlinear Observer for Simultaneous Localization and Mapping
نویسندگان
چکیده
A geometric nonlinear observer algorithm for Simultaneous Localization and Mapping (SLAM) developed on the Lie group of \mathbb{SLAM}_{n}\left(3\right) is proposed. The presented novel solution estimates vehicle's pose (i.e. attitude position) with respect to landmarks simultaneously positioning reference features in global frame. proposed estimator manifold characterized by predefined measures transient steady-state performance. Dynamically reducing boundaries guide error function system reduce asymptotically origin from its starting position within a large given set. has ability use available velocity feature measurements directly. Also, it compensates unknown constant bias attached measurements. Unit-qauternion presented. Numerical results reveal effectiveness observer. Keywords: Nonlinear filter algorithm, Mapping, estimator, SLAM manifold, matrix Group, design, asymptotic stability, systematic convergence, Prescribed performance function, estimation, filter, landmark gradient based observer, SLAM, adaptive estimate, framework, equivariant inertial vision unit, visual, SE(3), SO(3).
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ژورنال
عنوان ژورنال: IEEE Control Systems Letters
سال: 2021
ISSN: ['2475-1456']
DOI: https://doi.org/10.1109/lcsys.2020.3000266