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Invariant filtering for wheeled vehicle localization with unknown wheel radius and unknown GNSS lever arm

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arxiv 2409.07050 v1 pith:GUVGIUZ4 submitted 2024-09-11 cs.RO

classification cs.RO
keywords invariantunknownfilteringwheelgnsskalmanpositionproblem
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We consider the problem of observer design for a nonholonomic car (more generally a wheeled robot) equipped with wheel speeds with unknown wheel radius, and whose position is measured via a GNSS antenna placed at an unknown position in the car. In a tutorial and unified exposition, we recall the recent theory of two-frame systems within the field of invariant Kalman filtering. We then show how to adapt it geometrically to address the considered problem, although it seems at first sight out of its scope. This yields an invariant extended Kalman filter having autonomous error equations, and state-independent Jacobians, which is shown to work remarkably well in simulations. The proposed novel construction thus extends the application scope of invariant filtering.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Classification of Linear Observed Systems on Multi-Frame Groups via Automorphisms

    eess.SY 2024-12 conditional novelty 7.0 of 10

    All group-affine dynamics and algebraic observations on multi-frame groups are classified via automorphisms, extending two-frame group theory to coupled multi-frame navigation.

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