Design and development of an on-board autonomous visual tracking system for unmanned aerial vehicles

References

• Abhari, S. Q.; Qazvin-Iran; Ershadi, T. Z. 2011. Target Tracking Based on Mean Shift and KALMAN Filter with Kernel Histogram Filtering, Computer and Information Science 4(2): 152–160. https://doi.org/10.5539/cis.v4n2p152
   Google Scholar
• Al-Radaideh, A.; Al-Jarrah, M. A.; Jhemi, A.; Dhaouadi, R. 2009. ARF60 AUS-UAV modeling, system identification, guidance and control: validation through hardware in the loop simulation’, in International Symposium on Mechatronics and its Applications, 23–26 March 2009, Sharjah, UAE.
   Google Scholar
• Al-Radaideh, A. 2009. Guidance, control and trajectory tracking of small fixed wing unmanned aerial vehicles (UAVs): MSc thesis. American University of Sharjah.
   Google Scholar
• Athulathmudali, K. 2008. Flight control software design for small high endurance science flight vehicle: MSc thesis. School of Engineering, Cranfield University.
   Google Scholar
• AVDS [online]. 2016 [cited 17 December 2016]. Available from Internet: http://www.rassimtech.com
   Google Scholar
• Beard, R.; Kingston, D.; Quigley, M.; Snyder, D.; Christiansen, R.; Johnson, W.; McLain, T.; Goodrich, M. A. 2005. Autonomous vehicle technologies for small fixed-wing UAVs, Journal of Aerospace Computing, Information, and Communication 2(1): 92–108. https://doi.org/10.2514/1.8371
   Google Scholar
• Brake, N. J. 2012. Control system development for small uav gimbal: MSc thesis. Department of Aerospace Engineering, California Polytechnic State University, San Luis Obispo.
   Google Scholar
• Chao, H.; Cao, Y.; Chen, Y. 2007. Autopilots for small fixed-wing unmanned air vehicles: a survey, in Proc. of the IEEE International Conference on Mechatronics and Automation, 5–8 August 2007, Harbin, China. https://doi.org/10.1109/ICMA.2007.4304064
   Google Scholar
• Christiansen, R. S. 2004. Design of an autopilot for small unmanned aerial vehicles: MSc thesis. Department of Electrical and Computer Engineering, Brigham Young University.
   Google Scholar
• Chuan, L. H. 2009. Robustness of control laws implemented in visual based target tracking system: MSc thesis. Department of Mechanical and Astronautical Engineering, Naval Postgraduate School, Monterey, California.
   Google Scholar
• Cohen, I.; Medioni, G. 1998. Detecting and tracking moving objects in video from and airborne observer, in IEEE Image Understanding Workshop, 217–222.
   Google Scholar
• Comaniciu, D.; Meer, P. 1999. Mean shift analysis and applications, in IEEE International Conference Computer Vision, 1999, Kerkyra, Greece. https://doi.org/10.1109/ICCV.1999.790416
   Google Scholar
• Comaniciu, D.; Ramesh, V.; Meer, P. 2000. Real-time tracking of non-rigid objects using mean shift, in Proc. of the Conference on Computer Vision and Pattern Recognition, 2000. https://doi.org/10.1109/CVPR.2000.854761
   Google Scholar
• Comaniciu, D.; Meer, P. 2002. Mean shift: a robust approach toward feature space analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence 24(5): 603–619. https://doi.org/10.1109/34.1000236
   Web of Science ®Google Scholar
• Comaniciu, D.; Ramesh, V.; Meer, P. 2003. Kernel-based object tracking, IEEE Transactions on Pattern Analysis and Machine Intelligence 25(5): 564–577. https://doi.org/10.1109/TPAMI.2003.1195991
   Web of Science ®Google Scholar
• Dobrokhodov, V. N.; Kaminer I. I.; Jones, K. D.; Ghabcheloo, R. 2006. Vision-based tracking and motion estimation for moving targets using small UAVs, in American Control Conference, 14–16 June 2006, Minneapolis, USA.
   Google Scholar
• El-Kalubi, A. A.; Zhou, R.; Sun, H. 2011. Vision-based real time guidance of UAV, in International Conference on Management and Service Science, 2011, Wuhan, China. https://doi.org/10.1109/ICMSS.2011.5999382
   Google Scholar
• FlightGear [online]. 2016 [cited 17 December 2016]. Available from Internet: http://www.flightgear.org
   Google Scholar
• Garcia, R. A. 2012. Gimbal control: MSc thesis. School of Engineering, Cranfield University.
   Google Scholar
• Intel. 2010. OpenCV Reference Manual v2.1. [March 18, 2010]. Intel Corporation.
   Google Scholar
• Janabi, F.; Marey, M. 2010. A Kalman Filter based method for pose estimation in visual servoing, IEEE Transactions on Robotics 26(5): 939–947. https://doi.org/10.1109/TRO.2010.2061290
   Web of Science ®Google Scholar
• Johansen, I. H. 2012. Autopilot design for unmanned aerial vehicles: MSc thesis. Department of Engineering Cybernetics, Norwegian University of Science and Technology.
   Google Scholar
• Kalman, R. E. 1960. A new approach to linear filtering and prediction problems, Transactions of ASME, Series D, Journal of Basic Engineering 82(1): 35–45. https://doi.org/10.1115/1.3662552
   Google Scholar
• Kalman, R. E.; Bucy R. S. 1961. New results in linear filtering and prediction theory, Transactions of ASME, Series D, Journal of Basic Engineering 83(1): 95–108. https://doi.org/10.1115/1.3658902
   Google Scholar
• Kemsaram, N.; Thatiparti, T. V. R.; Guntupalli, D. R. 2014a. A comparative study on image fusion algorithms for avionics applications, International Journal of Advanced Engineering and Global Technology 2(4): 616–621.
   Google Scholar
• Kemsaram, N.; Thatiparti, T. V. R.; Guntupalli, D. R. 2014b. An experimental study of the autonomous visual target tracking algorithms for small unmanned aerial vehicles, in Proc. of the Elsevier International Conference on Rough Sets and Knowledge Technologies, 9–11 November 2014, Hyderabad, India.
   Google Scholar
• Kemsaram, N.; Thatiparti, T. V. R.; Guntupalli, D. R. 2015. Autonomous visual tracking with extended Kalman Filter estimator for micro aerial vehicles, in Proc. of the Springer International Conference on Fuzzy and Neuro Computing, 16–19 December 2015, Hyderabad, India.
   Google Scholar
• Kemsaram, N.; Thatiparti, T. V. R.; Guntupalli, D. R. 2016a. A mean-shift algorithm based autonomous visual tracking for micro aerial vehicles, International Journal of Recent Trends in Engineering & Research 2(4): 362–369.
   Google Scholar
• Kemsaram, N.; Thatiparti, T. V. R.; Guntupalli, D. R.; Kuvvarapu, A. 2016b. An autonomous visual tracking algorithm based on mean-shift algorithm and extended Kalman filter estimator, International Journal of Innovative Computer Science & Engineering 3(2): 14–23.
   Google Scholar
• Kemsaram, N.; Thatiparti, T. V. R.; Guntupalli, D. R.; Kuvvarapu, A. 2016c. An efficient approach of autonomous visual tracking for micro aerial vehicles, International Journal of Recent Scientific Research 7(6): 11959–11964.
   Google Scholar
• Kemsaram, N.; Thatiparti, T. V. R.; Guntupalli, D. R.; Kuvvarapu, A. 2016d. A hybrid autonomous visual tracking algorithm for micro aerial vehicles, International Journal of Engineering Sciences & Research Technology 5(8): 524–535.
   Google Scholar
• Kemsaram, N.; Thatiparti, T. V. R.; Guntupalli, D. R.; Kuvvarapu, A. 2017. A multi-level visual tracking algorithm for autonomous vehicles, International Journal of Advanced Research in Computer Science 8(7): 1156–1162. https://doi.org/10.26483/ijarcs.v8i7.4421
   Google Scholar
• Li, Z.; Hovakimyan, N.; Dobrokhodov, V.; Kaminer, I. 2010. Vision-based target tracking and motion estimation using a small UAV, in IEEE Conference on Decision and Control, 15–17 December 2010, Atlanta, GA. https://doi.org/10.1109/CDC.2010.5718149
   Google Scholar
• Mandrekar, A. 2008. Autonomous flight control system for an unmanned aerial vehicle: MSc thesis. School of Engineering, Cranfield University.
   Google Scholar
• Paris, S.; Durand, F. 2007. A topological approach to hierarchical segmentation using mean shift, in IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 17–22 June 2007, Minneapolis, USA. https://doi.org/10.1109/CVPR.2007.383228
   Google Scholar
• Peliti, P.; Rosa, L.; Oriolo, G.; Vendittelli, M. 2012. Vision-based loitering over a target for a fixed-wing UAV, in IFAC Symposium on Robot Control, International Federation of Automatic Control, 5–7 September 2012, Dubrovnik, Croatia. https://doi.org/10.3182/20120905–3-HR-2030.00036
   Google Scholar
• Prince, R. A. 2004. Autonomous visual tracking of stationary targets using small unmanned aerial vehicles: MSc thesis. Department of Mechanical and Astronautical Engineering, Naval Postgraduate School, Monterey, California.
   Google Scholar
• Qadir, A.; Neubert, J.; Semke, W. 2011. On-board visual tracking with unmanned aircraft system, in AIAA Infotech@ Aerospace Conference, 29–31 March 2011, St. Louis, MO.
   Google Scholar
• Quek, C. K. 2005. Vision based control and target range estimation for small unmanned aerial vehicle: MSc thesis. Department of Mechanical and Astronautical Engineering, Naval Postgraduate School, Monterey, California.
   Google Scholar
• Qureshi, S. 2008. The design of a trajectory following controller for unmanned aerial vehicles: MSc thesis. School of Engineering, Cranfield University.
   Google Scholar
• Regina, N. 2011. New target tracking and monitoring guidance laws for UAV. Dipartimento di Elettronica, Informatica e Sistemistica Viale Risorgimento, Bologna, Italia.
   Google Scholar
• Saban, D. 2006. Flight control system design for the “demon” vehicle: MSc thesis. School of Engineering, Cranfield University.
   Google Scholar
• Salhi, A.; Jammoussi, A. Y. 2012. Object tracking system using camshift, meanshift and Kalman Filter, World Academy of Science, Engineering and Technology 6(4): 421–426.
   Google Scholar
• Tay, B. C. 2006. Development and implementation of new control law for vision based target tracking system onboard small unmanned aerial vehicles: MSc thesis. Department of Mechanical and Astronautical Engineering, Naval Postgraduate School, Monterey, California.
   Google Scholar
• Theodorakopoulos, P.; Lacroix, S. 2008. A strategy for tracking a ground target with a uav, in IEEE International Conference on Intelligent Robots and Systems, 22–26 September 2008, Nice, France. https://doi.org/10.1109/IROS.2008.4650939
   Google Scholar
• Wang, B., 2011. Multi-target tracking using multi-camera system: MSc thesis. School of Engineering, Cranfield University.
   Google Scholar
• Wang, X.; Zhu, H.; Zhang, D.; Zhou, D.; Wang, X. 2014. Vision-based detection and tracking of a mobile ground target using a fixed-wing UAV, International Journal of Advanced Robotic Systems 11(156): 1–11. https://doi.org/10.5772/58989
   Google Scholar
• Watkiss, E. J. 1994. Flight dynamics of an unmanned aerial vehicle: MSc thesis. Department of Aeronautical Engineering, Naval Postgraduate School, Monterey, California.
   Google Scholar
• Welch, G.; Bishop, G. 2001. An introduction to the Kalman Filter, in Proceedings of SIGGRAPH, 12–17 August 2001, Los Angeles, CA.
   Google Scholar
• Xin, Z.; Fang, Y.; Xian, B. 2011. An on-board pan-tilt controller for ground target tracking systems, in IEEE International Conference on Control Applications, 28–30 September 2011, CO, USA. https://doi.org/10.1109/CCA.2011.6044390
   Google Scholar
• Yau, W. G.; Fu, L.-C.; Liu, D. 2001. Design and implementation of visual servoing system for realistic air target tracking, in Proc. of the IEEE International Conference on Robotics and Automation, 21–26 May 2001, Seoul, South Korea.
   Google Scholar
• Zhang, M.; Liu, H. H. T. 2010. Vision-based tracking and estimation of ground moving target using unmanned aerial vehicle, in American Control Conference, 30 June – 2 July 2010, Baltimore, MD, USA.
   Google Scholar