Fusion of Optical Flow and Inertial Measurements for Robust Egomotion Estimation
Abstract
In this paper we present a method for fusing optical flow and inertial measurements. To this end, we derive a novel visual error term which is better suited than the standard continuous epipolar constraint for extracting the information contained in the optical flow measurements. By means of an unscented Kalman filter (UKF), this information is then tightly coupled with inertial measurements in order to estimate the egomotion of the sensor setup. The individual visual landmark positions are not part of the filter state anymore. Thus, the dimensionality of the state space is significantly reduced, allowing for a fast online implementation. A nonlinear observability analysis is provided and supports the proposed method from a theoretical side. The filter is evaluated on real data together with ground truth from a motion capture system. Show more
Permanent link
https://doi.org/10.3929/ethz-a-010184819Publication status
publishedPublisher
ETH-ZürichSubject
COMPUTER VISION + SCENE UNDERSTANDING (ARTIFICIAL INTELLIGENCE); DIGITALE BILDVERARBEITUNG; DIGITAL IMAGE PROCESSING; COMPUTERVISION (KÜNSTLICHE INTELLIGENZ)Organisational unit
03737 - Siegwart, Roland Y. / Siegwart, Roland Y.
Notes
ASL; State Estimation; Optical Flow.More
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