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Warianty tytułu
Języki publikacji
Abstrakty
Computer vision is one of the main research fields for micro air vehicles. Therefore many teams around the globe are developing different camera systems which are directly mounted on a MAV or observe and track it from a fixed position. This paper presents a simple and cheap solution for a precise 40 gram onboard computer vision system based on a 6 gram Gumstix Overo Firestorm computer, a 23 gram infrared camera a custom adapter board including buck converter and connectors and three ground based high power infrared LED’s. It has great potential for educational applications because no fixed and calibrated camera installation around the flight area is necessary so it can easily be deployed and removed. The use of various filter algorithms makes it very reliable and the 752x480 pixel images are processed with 12 fps. The achieved accuracy is about 2% and the range was tested up to 10 m.
Rocznik
Tom
Strony
46--52
Opis fizyczny
Bibliogr. 11 poy., rys.
Twórcy
autor
- Department of Embedded Systems, University of Applied Sciences Technikum Wien, Vienna, Austria
autor
- Department of Embedded Systems, University of Applied Sciences Technikum Wien, Vienna, Austria
autor
- Department of Embedded Systems, University of Applied Sciences Technikum Wien, Vienna, Austria
Bibliografia
- [1] G. Freudenberger, Sensor Fusion für ein MEMSbasiertes Trägheits-navigationssystem, Master’s thesis, University of Applied Sciences Technikum Wien, 2012.
- [2] N. Vavra, Guidance, Navigation and Control of a Micro Air Vehicle, Master’s thesis, University of Applied Sciences Technikum Wien, 2012.
- [3] RobotChallenge Organization Team, “RobotChallenge 2013 Air Race Rules”, http://www.robotchallenge. org/competition/
- [4] L. Meier, P. Tanskanen, F. Fraundorfer, M. Pollefeys, “PIXHAWK: A System for Autonomous Flight using Onboard Computer Vision.” In: IEEE International Conference on Robotics and Automation, 2011. DOI: http://dx.doi.org/10.1109/ICRA.2011.5980229
- [5] M. Kara, S. Patra, A. Lanzon, “Designing Simple Indoor Navigation System for UAVs.” In: 19th Mediterranean Conference on Control and Automation,2011.
- [6] G. Ducard, “Autonomous quadrotor flight using a vision system and accommodating frames misalignment.” In: Industrial Embedded Systems, IEEE International Symposium, 2009. DOI:http://dx.doi.org/10.1109/SIES.2009.5196224
- [7] S. Lupashin, “The Flying Machine Arena as of 2010.” In: IEEE International Conference on Robotics and Automation, 2011. DOI: http://dx.doi.org/10.1109/ICRA.2011.5980308
- [8] J. Faigl, T. Krajnik, J. Chudoba, M. Saska, “Low-Cost Embedded System for Relative Localization in Robotic Swarms.” In: IEEE International Conference on Robotics and Automation, Karlsruhe,2013. DOI: http://dx.doi.org/10.1109/ICRA.2013.6630694
- [9] I. Culjak, “A brief introduction to OpenCV.” In:MIPRO. Proceedings of the 35th International Convention, 2012.
- [10] R. Haralick, C. Lee, K. Ottenberg, M. Nölle, “Review and Analysis of Solutions of the Three Point Perspective Pose Estimation Problem”, International Journal of Computer Vision, vol. 13, no. 3, 1994, Kluwer Academic Publishers, 331–356. DOI: http://dx.doi.org/10.1007/BF02028352
- [11] R. Zarits, Kamerabasierte Positionsbestimmung und Speicherung der Bilddaten auf einem Micro Air Vehicle, Master’s thesis, University of Applied Sciences Technikum Wien, 2012.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5b804b7e-b863-44e1-8470-6aac878c42fa