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Continuous fusion of motion data using an axis-angle rotation representation with uniform B-spline

Hu, Haohao 1; Beck, Johannes; Lauer, Martin ORCID iD icon 1; Stiller, Christoph 1
1 Institut für Mess- und Regelungstechnik mit Maschinenlaboratorium (MRT), Karlsruher Institut für Technologie (KIT)


The fusion of motion data is key in the fields of robotic and automated driving. Most existing approaches are filter-based or pose-graph-based. By using filter-based approaches, parameters should be set very carefully and the motion data can usually only be fused in a time forward direction. Pose-graph-based approaches can fuse data in time forward and backward directions. However, pre-integration is needed by applying measurements from inertial measurement units. Additionally, both approaches only provide discrete fusion results. In this work, we address this problem and present a uniform B-spline-based continuous fusion approach, which can fuse motion measurements from an inertial measurement unit and pose data from other localization systems robustly, accurately and efficiently. In our continuous fusion approach, an axis-angle is applied as our rotation representation method and uniform B-spline as the back-end optimization base. Evaluation results performed on the real world data show that our approach provides accurate, robust and continuous fusion results, which again supports our continuous fusion concept.

Verlagsausgabe §
DOI: 10.5445/IR/1000136123
Veröffentlicht am 12.08.2021
DOI: 10.3390/s21155004
Zitationen: 1
Web of Science
Zitationen: 1
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Mess- und Regelungstechnik (MRT)
Institut für Mess- und Regelungstechnik mit Maschinenlaboratorium (MRT)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2021
Sprache Englisch
Identifikator ISSN: 1424-8220
KITopen-ID: 1000136123
Erschienen in Sensors
Verlag MDPI
Band 21
Heft 15
Seiten 5004
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
Schlagwörter uniform B-spline; data fusion; ego-motion estimation; axis-angle; Rodrigues’ formula; inertial measurement units (IMU); Simultaneous Localization and Mapping (SLAM)
Nachgewiesen in Web of Science
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