A Geometric Observer Design for Visual Localisation and Mapping
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van Goor, Pieter
Mahony, Robert
Hamel, Tarek
Trumpf, Jochen
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IEEE
Abstract
This paper builds on recent work on Simultaneous Localisation and Mapping (SLAM) in the non-linear observer community, by framing the visual localisation and mapping problem as a continuous-time equivariant observer design problem on the symmetry group of a kinematic system. The state-space is a quotient of the robot pose expressed on SE (3) and multiple copies of real projective space, used to represent both points in space and bearings in a single unified framework. An observer with decoupled Riccati-gains for each landmark is derived and we show that its error system is almost globally asymptotically stable and exponentially stable in-the-large.
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Proceedings of the 58th IEEE Conference on Decision and Control, CDC 2019
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2099-12-31