NDLI: Robust calibration of an ultralow-cost inertial measurement unit and a camera: Handling of severe system uncertainty

Content Provider	IEEE Xplore Digital Library
Author	Chang-Ryeol Lee Ju Hong Yoon Kuk-Jin Yoon
Copyright Year	2014
Description	Author affiliation: Sch. of Inf. & Commun., Gwang-ju Inst. of Sci. & Technol., Gwangju, South Korea (Chang-Ryeol Lee; Ju Hong Yoon; Kuk-Jin Yoon)
Abstract	Recently, mobile devices such as smart phones and quad-copters are being equipped with inertial measurement units (IMUs) because of advances in micro-electro-mechanical systems technology. This has increased the importance of IMU- camera fusion for vision-based applications. However, ultralow-cost IMUs take much less accurate measurements than low-cost and high-cost IMUs. This uncertainty degrades the accuracy and reliability of IMU-camera calibration, which is the most important step for IMU-camera fusion technology. In this paper, we propose three effective algorithms for robust IMU- camera calibration with uncertain measurements: boundary constraint, adaptive prediction, and angular velocity constraint. These algorithms incorporate a Bayesian filtering framework to estimate calibration parameters more efficiently. The experimental results on both simulation and real data demonstrated the superiority of the proposed algorithms.
Starting Page	3020
Ending Page	3026
File Size	1018378
Page Count	7
File Format	PDF
ISBN	9781479936854
DOI	10.1109/ICRA.2014.6907294
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-05-31
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Calibration Cameras Noise Angular velocity Noise measurement Vectors Three-dimensional displays
Content Type	Text
Resource Type	Article

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