Iterative bias estimation for an ultra-wideband localization system

Title

Iterative bias estimation for an ultra-wideband localization system

 Author

van der Heijden, D.S. (TU Delft Learning & Autonomous Control)
Ledergerber, Anton (ETH Zürich)
Gill, Rajan (ETH Zürich)
D'Andrea, Raffaello (ETH Zürich)

Date

2021

 Abstract

An iterative bias estimation framework is presented that mitigates position-dependent ranging errors often present in ultra-wideband localization systems. State estimation and control are integrated, such that the positioning accuracy improves over iterations. The framework is experimentally evaluated on a quadcopter platform, resulting in improvements in the tracking performance with respect to ground truth, and also smoothing the overall flight by significantly reducing unwanted oscillations; see https://youtu.be/J-htfbzf40U for a video.


 Subject

Adaptive observer design
Bayesian methods
Classification
Iterative and repetitive control
Recursive least squares
Sensor fusion
Ultra-wideband technology

 To reference this document use:

http://resolver.tudelft.nl/uuid:d4de99ca-f6a2-4e74-ab21-69a83cc8a681

 DOI

https://doi.org/10.1016/j.ifacol.2020.12.1889

 ISSN

1474-6670

 Source

IFAC-PapersOnLine, 53 (2020) (2), 1391-1396

 Event

21st IFAC World Congress 2020, 2020-07-12 → 2020-07-17, Berlin, Germany

 Part of collection

Institutional Repository

 Document type

journal article

 Rights

© 2021 D.S. van der Heijden, Anton Ledergerber, Rajan Gill, Raffaello D'Andrea
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