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Information filtering with submaps for inertial aided visual odometry

: Kleinert, Markus; Stilla, Uwe

Volltext urn:nbn:de:0011-n-3364355 (827 KByte PDF)
MD5 Fingerprint: f370d78331ddb74bcf4900f35cf1695f
Erstellt am: 16.4.2015

Stilla, U. ; International Society for Photogrammetry and Remote Sensing -ISPRS-:
PIA 2015, Photogrammetric Image Analysis : HRIGI15 - High Resolution Earth Imaging for Geospatial Information, workshops, 25-27 March 2015, Munich, Germany
Istanbul: ISPRS, 2015 (ISPRS Annals II-3/W4)
Workshop "Photogrammetric Image Analysis" (PIA) <2015, Munich>
Workshop "High Resolution Earth Imaging for Geospatial Information" (HRIGI) <2015, Munich>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()
indoor positioning; inertial aided visual odometry; bundle adjustment; submapping

This work is concerned with the fusion of inertial measurements (accelerations and angular velocities) with imagery data (feature points extracted in a video stream) in a recursive bundle adjustment framework for indoor position and attitude estimation. Recursive processing is achieved by a combination of local submaps and the Schur complement. The Schur complement is used to reduce the problem size at regular intervals while retaining the information provided by past measurements. Local submaps provide a way to propagate the gauge constraints and thereby to alleviate the detrimental effects of linearization errors in the prior. Though the presented technique is not real-time capable in its current implementation, it can be employed to process arbitrarily long trajectories. The presented system is evaluated by comparing the estimated trajectory of the system with a reference trajectory of a prism attached to the system, which was recorded by a total station.