Abstract
Cameras and Inertial Measurement Units are widely used for motion tracking and general activity recognition. Sensor fusion techniques, which employ both Vision- and IMU-based tracking, rely on their precise synchronization in time and relative pose calibration. In this work, we propose a novel technique for solving both time and relative pose calibration between an optical target (OT) and an inertial measurement unit (IMU). The optical tracking system gathers 6DoF position and rotation data of the OT and the proposed approach uses them to simulate accelerometer and gyroscope readings to compare them against real ones recorded from the IMU. Convergence into the desired result of relative pose calibration is achieved using the adaptive genetic algorithm.
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ART System User Manual, version 2.1, April 2015.
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M-G350-PD11 Datasheet, 21 October 2012.
References
Alves, J., Lobo, J., Dias, J.: Camera-inertial sensor modelling and alignment for visual navigation. Mach. Intell. Robotic Control 5(3), 103–112 (2003)
Dam, E.B., Koch, M., Lillholm, M.: Quaternions, Interpolation and Animation. Københavns Universitet, Datalogisk Institut (1998)
Davis, L.: Handbook of Genetic Algorithms, 1st edn. Van Nostrand Reinhold, New York (1991)
Hol, J.D., Schön, T.B., Gustafsson, F.: Modeling and calibration of inertial and vision sensors. Int. J. Robotics Res. 29(2–3), 231–244 (2010)
Kelly, J., Sukhatme, G.S.: Fast relative pose calibration for visual and inertial sensors. In: Khatib, O., Kumar, V., Pappas, G.J. (eds.) Experimental Robotics, vol. 54, pp. 515–524. Springer, Heidelberg (2009)
Lobo, J., Dias, J.: Relative pose calibration between visual and inertial sensors. Int. J. Robotics Res. 26(6), 561–575 (2007)
McKinley, S., Levine, M.: Cubic spline interpolation. College Redwoods 45(1), 1049–1060 (1998)
Mirzaei, F.M., Roumeliotis, S.I.: A kalman filter-based algorithm for IMU-camera calibration: observability analysis and performance evaluation. IEEE Trans. Robotics 24(5), 1143–1156 (2008)
O’Haver, T.: A Pragmatic Introduction to Signal Processing. CreateSpace Independent Publishing Platform, North Charleston (1997)
Zheng, S., Chai, X., Su, S., Liu, X., Neta, K., Miller, W.: Relative pose calibration between inertial unit and visual unit in railway track inspection system. J. Balk. Tribological Assoc. 22(2), 1253–1264 (2016)
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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Pancholi, M., Dimitrov, S., Schmitz, N., Lampe, S., Stricker, D. (2017). Relative Translation and Rotation Calibration Between Optical Target and Inertial Measurement Unit. In: Magno, M., Ferrero, F., Bilas, V. (eds) Sensor Systems and Software. S-CUBE 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 205. Springer, Cham. https://doi.org/10.1007/978-3-319-61563-9_15
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DOI: https://doi.org/10.1007/978-3-319-61563-9_15
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