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Joint calibration of multiple sensors

Quoc V. Le, Andrew Y. Ng

Year
2009
Citations
54

Abstract

Many calibration methods calibrate a pair of sensors at a time. For robotic systems with many sensors, they are often time-consuming to use, and can also lead to inaccurate results. In this paper, we combine a number of ideas in the literature to derive a unified framework that jointly calibrates many sensors a large system. Key to our approach are (i) grouping sensors to produce 3D data, thereby providing a unifying formalism that allows us to jointly calibrate all of the groups at the same, (ii) using a variety of geometric constraints to perform the calibration, and (iii) sharing sensors between groups to increase robustness. We show that this gives a simple method that is easily applicable to calibrating large systems. Our experiments show that this method not only reduces calibration error, but also requires less human time.

Keywords

Robustness (evolution)Computer scienceCalibrationFormalism (music)Key (lock)AlgorithmArtificial intelligenceReal-time computingMathematics

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