Title :
Joint calibration of multiple sensors
Author :
Le, Quoc V. ; Ng, Andrew Y.
Author_Institution :
Comput. Sci. Dept., Stanford Univ., Stanford, CA, USA
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 :
calibration; manipulators; sensor fusion; geometric constraints; grouping sensors; joint sensor calibration; robotic systems; sharing sensors; Calibration; Cameras; Humans; Intelligent robots; Intelligent sensors; Optimization methods; Robot sensing systems; Robot vision systems; Robustness; Sensor systems;
Conference_Titel :
Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on
Conference_Location :
St. Louis, MO
Print_ISBN :
978-1-4244-3803-7
Electronic_ISBN :
978-1-4244-3804-4
DOI :
10.1109/IROS.2009.5354272