Алгоритм навигации беспилотного летательного аппарата на основе улучшенного алгоритма…
ISSN 0236-3933. Вестник МГТУ им. Н.Э. Баумана. Сер. Приборостроение. 2017. № 3
93
REFERENCES
[1] Cheeseman P., Smith R., Self M. A stochastic map for uncertain spatial relationships.
4th Int.
Symp. on Robotic Research
, 1987, pp. 467–474.
[2] Biswas J., Veloso M. Depth camera based indoor mobile robot localization and navigation.
IEEE
Int. Conf. on Robotics and Automation
, 2012, pp. 1697–1702. DOI: 10.1109/ICRA.2012.6224766
Available at:
http://ieeexplore.ieee.org/document/6224766[3] Tu Y., Huang Z., Zhang X., et al. The mobile robot SLAM based on depth and visual sensing in
structured environment.
Robot Intelligence Technology and Applications 3
, 2015, pp. 343–357.
DOI: 10.1007/978-3-319-16841-8_32 Available at:
https://link.springer.com/chapter/10.1007/978-3-319-16841-8_32
[4] Choi Y.W., Kim K.D., Choi J.W., Lee S.G. Laser image SLAM based on image matching for
navigation of a mobile robot.
Journal of the Korean Society for Precision Engineering
, 2013, vol. 30,
no. 2, pp. 177–184. DOI: 10.7736/KSPE.2013.30.2.177 Available at:
http://koreascience.or.kr/article/ArticleFullRecord.jsp?cn=JMGHBV_2013_v30n2_177
[5]
Fabresse F.R., Caballero F., Maza I., Ollero A. Localization and mapping for aerial manipulation
based on range-only measurements and visual markers.
IEEE Int. Conf. on Robotics and Automa-
tion (ICRA)
, 2014, pp. 2100–2106. DOI: 10.1109/ICRA.2014.6907147
Available at:
http://ieeexplore.ieee.org/document/6907147[6] Roh H.C., Sung C.H., Kang M.T., Chung M.J. Fast SLAM using polar scan matching and parti-
cle weight based occupancy grid map for mobile robot.
8th Int. Conf. on Ubiquitous Robots and
Ambient Intelligence (URAI)
, 2011, pp. 756–757. DOI: 10.1109/URAI.2011.6146004
Available at:
http://ieeexplore.ieee.org/document/6146004[7] Qu L., He S., Qu Y. An SLAM algorithm based on improved UKF.
24th Chinese Control and
Decision Conf. (CCDC)
, 2012, pp. 4154–4157. DOI: 10.1109/CCDC.2012.6243112
Available at:
http://ieeexplore.ieee.org/document/6243112[8] Chatterjee A., Ray O., Chatterjee A., Rakshit A. Development of a real-life EKF based SLAM
system for mobile robots employing vision sensing.
Expert Systems with Applications
, 2011, vol. 38,
no. 7, pp. 8266–8274. DOI: 10.1016/j.eswa.2011.01.007 Available at:
http://www.sciencedirect.com/science/article/pii/S0957417411000273
[9]
Sola J., Vidal-Calleja T., Civera J., Montiel J.M.M. Impact of landmark parametrization on
monocular EKF–SLAM with points and lines.
Int. Journal of Computer Vision
, 2012, vol. 97, no. 3,
pp. 339–368. DOI: 10.1007/s11263-011-0492-5
Available at:
https://link.springer.com/article/10.1007/s11263-011-0492-5[10]
Bailey T., Nieto J., Guivant J., Stevens M., Nebot E. Consistency of the EKF–SLAM algorithm.
IEEE/RSJ Int. Conf. on Intelligent Robots and Systems
, 2006, pp. 3562–3568.
DOI: 10.1109/IROS.2006.281644 Available at:
http://ieeexplore.ieee.org/document/4058955[11]
Ke Ke Geng. An improved EKF–SLAM algorithm for mobile robot.
Internauka,
2016, no. 2,
pp. 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, pp. 45–78. DOI: 10.1023/A:1007963824710
Available at:
https://link.springer.com/article/10.1023%2FA%3A1007963824710[14]
Geng Ke Ke, Chulin N.A. Environment reconstruction method with cloudy-point maps based
on real-time monocular computer vision.
Mezhdunarodnyy zhurnal eksperimental'nogo obra-
zovaniya
[International Journal of Experimental Education], 2015, no. 12-3, pp. 437–442.
Available at:
https://expeducation.ru/ru/article/view?id=9163