Binocular technical vision for wheeled robot controlling

• Autorzy: Kulik A. , Dergachov K. , Radomskyi O.

Warianty tytułu

RU

Бинокулярное техническое зрение для управления колесным роботом

• Języki publikacji: EN

Abstrakty

EN

Proposed model of technical vision system use for supplementation and clarifying information about surround objects classes and distances, received by driver.

RU

Предложена модель применения системы технического зрения для дополнения и уточнения информации, получаемой водителем транспортного средства, о характере и расстояниях до окружающих транспортное средство объектов.

Słowa kluczowe

EN

binocular technical vision; wheeled robot; controlling using camera

PL

widzenie obuoczne techniczne; robot na kółkach; sterowanie za pomocą aparatu

• Wydawca: Wydawnictwo Politechniki Śląskiej
• Czasopismo: Transport Problems
• Rocznik: 2015
• Tom: T. 10, z. 1
• Strony: 55--62
• Opis fizyczny: Bibliogr. 27 poz., rys.

Twórcy

autor

Kulik A.

• National Aerospace University "Kharkiv Aviation Institute", Chkalova str. 17, Kharkiv, 61070, Ukraine

autor

Dergachov K.

• National Aerospace University "Kharkiv Aviation Institute", Chkalova str. 17, Kharkiv, 61070, Ukraine

autor

Radomskyi O.

• National Aerospace University "Kharkiv Aviation Institute", Chkalova str. 17, Kharkiv, 61070, Ukraine

Bibliografia

• 1. Piecha, J. Digital camera as a data source of ITS solutions in traffic control and management. Transport Problems. 2012. Vol. 7. No. 3. P. 57-70.
• 2. Piecha, J. & Staniek, M. The syntactic alphabet analysis for vehicles simple and fast assignment. Proc of Int. Conf. on Telematics, Logistics & Transport Safety. Silesian University of Technology. Katowice. 2009. P. 51-57.
• 3. Gnyla, P. & Piecha, J. The Transportation Network Rough Description for an Adaptive Traffic Control Process by Means of Video Detection Technology. IV Int. Conf. “Transport Problems”. Silesian University of Technology. Katowice. 2012. P. 155-163.
• 4. Pamuła, W.: Object Classification Methods for Application in FPGA Based Vehicle Video Detector. Transport Problems. Vol. 4. No. 2. 2009. P. 5-14.
• 5. Piecha, J. & Staniek, M. Vehicles Trajectories Movement Description by Means of Syntactic Method. Transport Problems. 2009. Vol. 4. No. 4. P. 53-60.
• 6. Chilian, A & Hirshmüller, H. Stereo Camera Based Camera Naviagation of Mobile Robots on Rough Terrain. IEEE International Conference of Intelligent Robots and Systems (IROS). October 2009. St. Louis. MO. USA.
• 7. Beymer, D. & McLauchlan, P. & Coifman B. & Malik, J.A Real-time Computer Vision System for Measuring Traffic Parameters. Proc. of Int. Conf. Computer Vision and Pattern Recognition Workshops. 1997. P. 495-501.
• 8. Bos, I. & Ettema, D. & Molin, E. Modeling effect of travel time uncertainty and traffic information on use of park-and-ride facilities. Transportation Research Board. 2004. Vol. 1898. P. 37-44.
• 9. Burzyński, M. & Kosiński, W. & Schulz, T. & Zając, P. A highway traffic modeling by means of cellular automaton. In: Transactions on transport systems telematics and safety. Gliwice: Silesian University of Technology. 2009. P. 11-18.
• 10. Deng, L. & Tang, N. & Lee, D. & Wang, Ch. & Lu, M. Vision Based Adaptive Traffic Signal Control System Development. Proc. of Int. Conf. Parallel and Distributed Systems. Vol. 2. 2005. P. 634-638.
• 11. Chitturi, M.V. & Medina, J.C. & Benekohal, R. F. Effect of shadows and time of day on performance of video detection systems at signalized intersections. Transportation Research Part C. 2010. Vol. 18. P. 176-186.
• 12. Degang, C. & Zhang, L. & Zhao, S. & Hu, Q & Zhu, P. A Novel Algorithm of Finding Reducts with Fuzzy Rough Set. Transactions on Fuzzy Systems. 2011. No. 99. P. 385-389.
• 13. Gnyla, P. & Piecha, J. The Transportation Network Rough Description for an Adaptive Traffic Control Process by Means of Video Detection Technology. IV Int. Conf. “Transport Problems”. Katowice: Silesian University of Technology. 2012. P. 155-163.
• 14. Haag, M. & Nagel, H.H. Combination of Edge Element and Optical Flow Estimates for 3DModel- Based Vehicle Tracking in Traffic Image Sequences. International Journal of Computer Vision. 1999. Vol. 35. No. 3. P. 295-319.
• 15. Yao, J.T. & Yao, Y.Y. Induction of classification rules by granular computing. Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing (TSCTC'02) London: Springer-Verlag. 2002.
• 16. Bargiela, A. & Kosonen, I. & Pursula, M. & Peytchev, E. Granular analysis of traffic data for turning movements estimation. International Journal of Enterprise Information Systems. 2006. Vol. 2. No 2. P.13-27.
• 17. Bargiela, A. & Pedrycz, W. The roots of granular computing. Proceedings of the 2006 IEEE International Conf. on Granular Computing. 2006. P. 806-809.
• 18. Płaczek, B. The method of data entering into cellular traffic model for on-line simulation. In: Piecha, J. (ed.) Transactions on Transport Systems Telematics. Gliwice. 2006.
• 19. Płaczek, B. Selective data collection in vehicular networks for traffic control applications. Transportation Research Part C. 2012. Vol. 23. P. 14-28.
• 20. Piecha, J. & Gnyla, P. & Baca, M. Some traffic control proposals by means of fuzzy sets theory. Proc. of Central European Conf. on Information and Intelligent Systems – CECIIS. Zagreb. Sept. 2011.
• 21. Zhao, Y. & Kockelman, K.M. The propagation of uncertainty through travel demand models: an exploratory analysis. Annals of Regional Science. 2002. Vol. 36. P. 145-163.
• 22. Strat, T.M. Recovering the camera parameters from a transformation matrix. Proc. of DARPA Image Understanding Workshop. New Orleans. LA. 1984. P. 264-271.
• 23. Atkinson, K.E. An Introduction to Numerical Analysis. John Wiley and Sons. 1989.
• 24. Tilneac, M. & Dolga, V. & Grigorescu, S. & Bitea, M.A. 3D stereo vision measurements for weed-crop discrimination. Elektronika ir Elektrotechnika. 2012. Vol 123. No. 7. P. 9-12.
• 25. Hartley, R. Estimation of Relative Camera Positions for Uncalibrated Cameras. Proc. of ECCV- 92. In: Sandini G. (Ed.). LNCS-Series. 1992. Vol. 588. Berlin: Springer-Verlag.
• 26. Longuet-Higgins, H.C. A computer algorithm for reconstructing a scene from two projections. Nature. 1981. Vol. 293. P. 133-135.
• 27. Sutherland, I.E. Three dimensional data input by tablet. Proceedings of IEEE. 1974. Vol. 62. P. 453-461.