Iterative bias estimation for an ultra-wideband localization system

Journal article (2021)

Authors

D.S. van der Heijden Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering
Anton Ledergerber ETH Zürich
Rajan Gill ETH Zürich
Raffaello D'Andrea ETH Zürich
Research Group
Learning & Autonomous Control (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2021 D.S. van der Heijden, Anton Ledergerber, Rajan Gill, Raffaello D'Andrea
DOI: https://doi.org/10.1016/j.ifacol.2020.12.1889
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Published Date

2021

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Learning & Autonomous Control

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.