Best axes composition: Multiple gyroscopes imu sensor fusion to reduce systematic error

Marsel Faizullin, Gonzalo Ferrer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we propose an algorithm to combine multiple cheap Inertial Measurement Unit (IMU) sensors to calculate 3D-orientations accurately. Our approach takes into account the inherent and non-negligible systematic error in the gyroscope model and provides a solution based on the error observed during previous instants of time. Our algorithm, the Best Axes Composition (BAC), chooses dynamically the most fitted axes among IMUs to improve the estimation performance. We compare our approach with a probabilistic Multiple IMU (MIMU) approach, and we validate our algorithm in our collected dataset. As a result, it only takes as few as 2 IMUs to significantly improve accuracy, while other MIMU approaches need a higher number of sensors to achieve the same results.

Original languageEnglish
Title of host publication2021 10th European Conference on Mobile Robots, ECMR 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665412131
DOIs
Publication statusPublished - Aug 2021
Event10th European Conference on Mobile Robots, ECMR 2021 - Virtual, Bonn, Germany
Duration: 31 Aug 20213 Sep 2021

Publication series

Name2021 10th European Conference on Mobile Robots, ECMR 2021 - Proceedings

Conference

Conference10th European Conference on Mobile Robots, ECMR 2021
Country/TerritoryGermany
CityVirtual, Bonn
Period31/08/213/09/21

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