Алгоритм навигации беспилотного летательного аппарата на основе улучшенного алгоритма…
ISSN 0236-3933. Вестник МГТУ им. Н.Э. Баумана. Сер. Приборостроение. 2017. № 3
91
8.
Chatterjee A., Ray O., Chatterjee A., Rakshit A.
Development of a real-life EKF based SLAM sys-
tem for mobile robots employing vision sensing // Expert Systems with Applications. 2011. Vol. 38.
No. 7. P. 8266–8274. DOI: 10.1016/j.eswa.2011.01.007
URL:
http://www.sciencedirect.com/science/article/pii/S09574174110002739.
Sola J., Vidal-Calleja T., Civera J., Montiel J.M.M.
Impact of landmark parametrization on mo-
nocular EKF–SLAM with points and lines // Int. Journal of Computer Vision. 2012. Vol. 97. No. 3.
P. 339–368. DOI: 10.1007/s11263-011-0492-5
URL:
https://link.springer.com/article/10.1007/s11263-011-0492-510.
Consistency
of the EKF–SLAM algorithm / T. Bailey, J. Nieto, J. Guivant, M. Stevens, E. Nebot
//
IEEE/RSJ Int. Conf. on Intelligent Robots and Systems. 2006. P. 3562–3568.
DOI: 10.1109/IROS.2006.281644 URL:
http://ieeexplore.ieee.org/document/405895511.
Geng Ke Ke
. An improved EKF–SLAM algorithm for mobile robot // Интернаука. 2016. № 2.
С. 74–78.
12.
Krig S
. Computer vision metrics: Survey, taxonomy, and analysis. Apress, 2014.
13.
Smith S.M
.,
Brady J.M
. SUSAN — a new approach to lowlevel image processing // Int. Journal
of Computer Vision. 1997. Vol. 23. No. 1. P. 45–78. DOI: 10.1023/A:1007963824710
URL:
https://link.springer.com/article/10.1023%2FA%3A100796382471014.
Гэн Кэ Кэ, Чулин Н.А.
Метод реконструкции облачно-точечной карты окружающей сре-
ды на основе монокулярного компьютерного зрения в режиме реального времени // Меж-
дународный журнал экспериментального образования. 2015. № 12-3. С. 437–442.
URL:
https://expeducation.ru/ru/article/view?id=916315.
Di Stefano L., Mattoccia S., Mola M.
An efficient algorithm for exhaustive template matching
based on normalized cross correlation // Proc. 12th Int. Conf. on Image Analysis and Processing.
2003. P. 322–327. DOI: 10.1109/ICIAP.2003.1234070
URL:
http://ieeexplore.ieee.org/document/123407016.
Armangué X., Salvi J.
Overall view regarding fundamental matrix estimation // Image and
Vision Computing. 2003. Vol. 21. No. 2. P. 205–220. DOI: 10.1016/S0262-8856(02)00154-3
URL:
http://www.sciencedirect.com/science/article/pii/S026288560200154317.
Camera
calibration toolbox for Matlab // Vision.caltech: веб-сайт
URL:
http://www.vision.caltech.edu/bouguetj/calib_doc(дата обращения: 19.10.2016).
18.
Hartley R.I
. Estimation of relative camera positions for uncalibrated cameras // European Conf.
on Computer Vision. 1992. P. 579–587. DOI: 10.1007/3-540-55426-2_62
URL:
https://link.springer.com/chapter/10.1007/3-540-55426-2_62?no-access=true19.
Hartley R., Zisserman A.
Multiple view geometry in computer vision. Cambridge University
Press, 2003.
20.
Bunschoten R., Krose B.
Visual odometry from an omnidirectional vision system // IEEE Int.
Conf. on Robotics and Automation. 2003. Vol. 1. P. 577–583. DOI: 10.1109/ROBOT.2003.1241656
URL:
http://ieeexplore.ieee.org/document/124165621.
Nistér D., Naroditsky O., Bergen J.
Visual odometry // Proc. 2004 IEEE Computer Society Conf.
on Computer Vision and Pattern Recognition. 2004. No. 1. P. 652–659.
DOI: 10.1109/CVPR.2004.1315094 URL:
http://ieeexplore.ieee.org/document/131509422.
A solution
to the simultaneous localization and map building (SLAM) problem / M.G. Dis-
sanayake, P. Newman, S. Clark, H.F. Durrant-Whyte, M. Csorba // IEEE Transactions on Robotics
and Automation. 2001. Vol. 17. No. 3. P. 229–241. DOI: 10.1109/70.938381
URL:
http://ieeexplore.ieee.org/document/938381