Gyro-aided camera-odometer online calibration and localization

Publication Type:
Conference Proceeding
Citation:
Proceedings of the American Control Conference, 2017, pp. 3579 - 3586
Issue Date:
2017-06-29
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© 2017 American Automatic Control Council (AACC). In this paper, we introduce a novel factor-graph based multi-sensor fusion algorithm that optimally estimates camera-odometer extrinsic calibration (6 DOF rigid body transformation between the two sensors) and localization aided by MEMS gyroscope measurements. In particular, we rigorously derive the camera-odometer calibration node and factors from the camera and odometer measurements. Moreover, due to the significantly higher frequency of the gyro than those of the camera and odometer, we develop analytical gyro preintegration using unit quaternions to provide a relative-rotation factor (constraint) between consecutive camera/odometer keyframes. Note that in our proposed gyro preintegration theory, the time-varying bias is addressed systematically (instead of treated in ad-hoc way, e.g., simply assumed to be constant as in most literature). The proposed approach is broadly corroborated in real-world experiments.
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