Iterative bias estimation for an ultra-wideband localization system

Bas van der Heijden; Anton Ledergerber; Rajan Gill; Raffaello D'Andrea

doi:10.1016/j.ifacol.2020.12.1889

Iterative bias estimation for an ultra-wideband localization system

Bas van der Heijden^*, Anton Ledergerber, Rajan Gill, Raffaello D'Andrea

^*Corresponding author for this work

Learning & Autonomous Control

Research output: Contribution to journal › Conference article › Scientific › peer-review

5 Citations (Scopus)

22 Downloads (Pure)

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.

Original language	English
Pages (from-to)	1391-1396
Journal	IFAC-PapersOnline
Volume	53 (2020)
Issue number	2
DOIs	https://doi.org/10.1016/j.ifacol.2020.12.1889
Publication status	Published - 2021
Event	21st IFAC World Congress 2020 - Berlin, Germany Duration: 12 Jul 2020 → 17 Jul 2020

Keywords

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

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10.1016/j.ifacol.2020.12.1889

1-s2.0-S2405896320325039-main-1Final published version, 4.59 MBLicence: CC BY-NC-ND

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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.",

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AU - Ledergerber, Anton

AU - Gill, Rajan

AU - D'Andrea, Raffaello

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AB - 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.

KW - Adaptive observer design

KW - Bayesian methods

KW - Classification

KW - Iterative and repetitive control

KW - Recursive least squares

KW - Sensor fusion

KW - Ultra-wideband technology

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M3 - Conference article

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SN - 1474-6670

VL - 53 (2020)

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EP - 1396

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IS - 2

T2 - 21st IFAC World Congress 2020

Y2 - 12 July 2020 through 17 July 2020

ER -

Iterative bias estimation for an ultra-wideband localization system

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Keywords

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