Open Access
Issue
MATEC Web Conf.
Volume 75, 2016
2016 International Conference on Measurement Instrumentation and Electronics (ICMIE 2016)
Article Number 05001
Number of page(s) 6
Section Theory of Measurement Error
DOI https://doi.org/10.1051/matecconf/20167505001
Published online 01 September 2016
  1. L. Beran, P. Chmelar, and M. Dobrovolny, Navigation of robotic platform with using Inertial Measurement Unit and Direct Cosine Matrix, 56thInternation-al Symposium Electronics in Marine(Elmar), 56, 87–90 (2014) [Google Scholar]
  2. L. Beran, P. Chmelar, and L. Rejfek, Navigation of Robotics Platform using Monocular Visual Odometry, 25th International Conference Radioelektronika, 25, 213–216 (2015) [Google Scholar]
  3. J. Campbell et.al, A Robust Visual Odometry and Precipice Detection System Using Consumer-grade Monocular Vision, Robotics and Automation. ICRA 2005, 3421–3427, (2005) [Google Scholar]
  4. CH. Yang, M. Maimone, and L. Matthies, “Visual Odometry on the Mars Exploration Rovers,” Systems, Man and Cybernetics, 1, 903 (2005) [CrossRef] [Google Scholar]
  5. L. Rejfek, Z. Mosna, D. Kouba, J. Boska, and D. Buresova, Application of digital filters to check quality of the automatically scaled ionograms, Journal of Electrical Engineering, ISSN: 1335–3632, 66, 3 164–168 (2015) [CrossRef] [Google Scholar]
  6. J. Borenstein and L. Feng, Measurement and Correction of Systematic Odometry Errors in Mobile Robots, IEEE Transactions on Robotics and Automation, 12, 6 869–880, (1996) [Google Scholar]
  7. P. Chmelar, L. Beran, N. Kudriavtseva, The Laser Color Detection for 3D Range Scanning Using Gaussian Mixture Model, 25th International Conference Radioelektronika 2015, 25, 248–253 (2015) [CrossRef] [Google Scholar]
  8. P. ChmelarAnd M. Dobrovolny, The Fusion of Ultrasonic and Optical Measurement Devices for Autonomous Mapping. 2013, 23rd International Conference Radioelektronika, 23, 292–296 (2013) [Google Scholar]
  9. P. Chmelar, L. Beran, N. Kudriavtseva., “Projection of point cloud for basic object detection,” 56th International Symposium (ELMAR 2014), 56, 11–14 (2014) [Google Scholar]
  10. B. Gersdorf and U. Frese, A Kalman Filter for Odometry using a Wheel Mounted Inertial Sensor. 10th International Conference on Informatics in Control, Automation and Robotics, 10, (2013) [Google Scholar]
  11. J.Z. Sasiadek and P. Hartana, Sensor data fusion using Kalman filter, in, FUSION 2000. Proceedings of the Third International Conference, 3, (2000) [Google Scholar]
  12. L. Beran, P. Chmelar, and L. Rejfek, Navigation of Robotics Platform Using Advanced Image Processing Navigation Methods, V. Eccomas Thematic Conference on Computional Vision and Medical Image Processing(VIPIMAGE), 5, 341–346 (2015) [Google Scholar]

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