Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2022 25th International Conference on Information Fusion, FUSION 2022 |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (elektronisch) | 9781737749721 |
| Publikationsstatus | Veröffentlicht - 2022 |
| Extern publiziert | Ja |
| Veranstaltung | 25th International Conference on Information Fusion, FUSION 2022 - Linkoping, Schweden Dauer: 4 Juli 2022 → 7 Juli 2022 |
Publikationsreihe
| Name | 2022 25th International Conference on Information Fusion, FUSION 2022 |
|---|
Abstract
We present a versatile quaternion-based inertial orientation estimation filter (VQF). Inclination drift from gyroscope strapdown integration is corrected from specific force measurements that are low-pass filtered in an almost-inertial frame to effectively compensate for instantaneous accelerations and decelerations. Heading drift is corrected via a scalar heading offset. The resulting decoupled state representation enables simultaneous 6D and 9D orientation estimation. We systematically evaluated the method on a rich orientation estimation benchmark dataset and show that the proposed method clearly outperforms three of the currently most commonly adopted and accurate inertial orientation estimation filters. The filter is available as open-source software, and its parameters are tuned to work well for a wide range of movements and application scenarios. The fundamentally different filtering approach with a decoupled state representation and novel inclination correction resulted in an unprecedented level of accuracy, with 41% lower orientation estimation errors and a twice-as-high inclination accuracy compared to existing state-of-the-art methods. This facilitates new and exciting high-precision applications in the field of inertial motion tracking.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Maschinelles Sehen und Mustererkennung
- Informatik (insg.)
- Information systems
- Informatik (insg.)
- Signalverarbeitung
- Entscheidungswissenschaften (insg.)
- Informationssysteme und -management
Zitieren
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- Apa
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- BibTex
- RIS
2022 25th International Conference on Information Fusion, FUSION 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 25th International Conference on Information Fusion, FUSION 2022).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - VQF
T2 - 25th International Conference on Information Fusion, FUSION 2022
AU - Laidig, Daniel
AU - Weygers, Ive
AU - Bachhuber, Simon
AU - Seel, Thomas
N1 - Publisher Copyright: © 2022 International Society of Information Fusion.
PY - 2022
Y1 - 2022
N2 - We present a versatile quaternion-based inertial orientation estimation filter (VQF). Inclination drift from gyroscope strapdown integration is corrected from specific force measurements that are low-pass filtered in an almost-inertial frame to effectively compensate for instantaneous accelerations and decelerations. Heading drift is corrected via a scalar heading offset. The resulting decoupled state representation enables simultaneous 6D and 9D orientation estimation. We systematically evaluated the method on a rich orientation estimation benchmark dataset and show that the proposed method clearly outperforms three of the currently most commonly adopted and accurate inertial orientation estimation filters. The filter is available as open-source software, and its parameters are tuned to work well for a wide range of movements and application scenarios. The fundamentally different filtering approach with a decoupled state representation and novel inclination correction resulted in an unprecedented level of accuracy, with 41% lower orientation estimation errors and a twice-as-high inclination accuracy compared to existing state-of-the-art methods. This facilitates new and exciting high-precision applications in the field of inertial motion tracking.
AB - We present a versatile quaternion-based inertial orientation estimation filter (VQF). Inclination drift from gyroscope strapdown integration is corrected from specific force measurements that are low-pass filtered in an almost-inertial frame to effectively compensate for instantaneous accelerations and decelerations. Heading drift is corrected via a scalar heading offset. The resulting decoupled state representation enables simultaneous 6D and 9D orientation estimation. We systematically evaluated the method on a rich orientation estimation benchmark dataset and show that the proposed method clearly outperforms three of the currently most commonly adopted and accurate inertial orientation estimation filters. The filter is available as open-source software, and its parameters are tuned to work well for a wide range of movements and application scenarios. The fundamentally different filtering approach with a decoupled state representation and novel inclination correction resulted in an unprecedented level of accuracy, with 41% lower orientation estimation errors and a twice-as-high inclination accuracy compared to existing state-of-the-art methods. This facilitates new and exciting high-precision applications in the field of inertial motion tracking.
UR - http://www.scopus.com/inward/record.url?scp=85136562823&partnerID=8YFLogxK
U2 - 10.23919/fusion49751.2022.9841356
DO - 10.23919/fusion49751.2022.9841356
M3 - Conference contribution
AN - SCOPUS:85136562823
T3 - 2022 25th International Conference on Information Fusion, FUSION 2022
BT - 2022 25th International Conference on Information Fusion, FUSION 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 4 July 2022 through 7 July 2022
ER -