DOI QR코드

DOI QR Code

Cooperative Surveillance and Boundary Tracking with Multiple Quadrotor UAVs

복수 쿼드로터 무인기를 이용한 협업 감시 및 경계선 추종

  • Lee, Hyeon Beom (School of Mechanical and Aerospace Engineering and Institute of Advanced Aerospace Technology, Seoul National University) ;
  • Moon, Sung Won (School of Mechanical and Aerospace Engineering and Institute of Advanced Aerospace Technology, Seoul National University) ;
  • Kim, Woo Jin (School of Mechanical and Aerospace Engineering and Institute of Advanced Aerospace Technology, Seoul National University) ;
  • Kim, Hyoun Jin (School of Mechanical and Aerospace Engineering and Institute of Advanced Aerospace Technology, Seoul National University)
  • 이현범 (서울대학교 기계항공공학부 항공우주신기술연구소) ;
  • 문성원 (서울대학교 기계항공공학부 항공우주신기술연구소) ;
  • 김우진 (서울대학교 기계항공공학부 항공우주신기술연구소) ;
  • 김현진 (서울대학교 기계항공공학부 항공우주신기술연구소)
  • Received : 2013.02.20
  • Accepted : 2013.03.15
  • Published : 2013.05.01

Abstract

This paper investigates a boundary tracking problem using multiple quadrotor UAVs to detect and track the boundary of physical events. We set the boundary estimation problem as a classification problem of the region in which the physical events occur, and employ SVL (Support Vector Learning). We also demonstrate a velocity vector field which is globally attractive to a desired closed path with circulation at the desired speed and a virtual phase for stabilizing the collective configuration of the multiple quadrotors. Experimental results with multiple quadrotors show that this study provides good performance of the collective boundary tracking.

Keywords

References

  1. S. M. Brennan, A. M. Mielke, D. C. Torney, and A. B. Maccabe, "Radiation detection with distributed sensor netwroks," IEEE Computer, vol. 37, no. 8, pp. 57-59, 2004.
  2. C. J. Cannell, A. S. Gadre, and D. J. Stilwell, "Boundary tracking and rapid mapping of a thermal plume using an autonomous vehicle," IEEE Oceans 2006, Boston, USA, Sep. 18-21, 2006.
  3. S. Simie, "A learning theory approach to sensor networks," IEEE Pervasive Computing, vol. 2, no. 4, 2003.
  4. J. Yoo, W. Kim, and H. J. Kim, "Event-driven gaussian process for object localization in wireless sensor networks," IEEE/RSJ International Conference on Intelligent Robots and Systems, San francisco, USA, Sep. 2011.
  5. W. Kim, J. Yoo, and H. Kim, "Multi-target tracking using distributed support vector machine over wireless sensor networks," IEEE International Conference on Robotics and Automation, St. Paul, USA, May. 2012.
  6. D. Marthaler and A. L. Bertozzi, "Tracking environmental level sets with autonomous vehicles," In S. Butenko, R. Murphey and P. M. Pardalos, editors, Recent Developments in Cooperative Control and Optimization, Kluwer Academic Publishers, 2003.
  7. F. Zhang, E. Fiorelli, and N. E. Leonard, "Exploring scalar fields using multiple sensor platforms: tracking level curves," 46th IEEE Conference on Decision and Control, New Orleans, USA, Dec. 12-14, 2007.
  8. Z. Jin and A. L. Bertozzi, "Environmental boundary tracking and estimation using multiple autonomous vehicles," 46th IEEE Conference on Decision and Control, New Orleans, USA, Dec. 12-14, 2007.
  9. W. J. Kim, D. J. Kwak, and H. J. Kim, "Joint detection and tracking of boundaries using cooperative mobile sensor networks," IEEE International Conference on Robotics and Automation, 2013, to appear
  10. D. Lee, J. Kim, and H. J. Kim, "Depth estimation for image-based visual servoing of an under-actuated system," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 18, no. 1, pp. 42-46, 2012. https://doi.org/10.5302/J.ICROS.2012.18.1.042
  11. J. H. Hwang, S. Hwang, S. K. Hong, and M. G. Yoo, "Attitude stabilization performance improvement of the quadrotor flying robot," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 18, no. 6, pp. 608-611, 2012. https://doi.org/10.5302/J.ICROS.2012.18.6.608
  12. S. Bouabdallah, A. Noth, and R. Siegwart, "PID vs LQ control techniques applied to an indoor micro quadrotor," IEEE/RSJ International Conference on Intelligent Robots and Systems, Sendai, Japan, Sep. 2004.
  13. D. Lee, H. J. Kim, and S. Sastry, "Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter," International Journal of Control, Automation and Systems, vol. 7, no. 3, pp. 419-428, 2009. https://doi.org/10.1007/s12555-009-0311-8
  14. T. Lee, M. Leoky, and N. McClamroch, "Geometric tracking control of a quadrotor uav on SE(3)," IEEE Conference on Decision and Control, Atlanta, USA, Dec. 2010.
  15. H. Lee, S. Kim, T. Ryan, and H. J. Kim, "Backstepping control based on SE(3) of a micro quadrotor for stable trajectory tracking," AIAA Guidance, Navigation, and Control, 2013, submitted.
  16. H. Lim, H. Lee, and H. J. Kim, "Onboard flight control of a micro quadrotor using single strapdown optical ow sensor," IEEE/RSJ International Conference on Intelligent Robots and Systems, Vilamoura, Portugal, Oct. 2012.
  17. D. A. Paley, N. E. Leonard, R. Sepulchre, D. Grunbaum, and J. K. Parrish, "Oscillator models and collective motion," IEEE Control Systems Magazine, pp. 89-105, Aug. 2007.

Cited by

  1. Experimental Verification of Multi-Sensor Geolocation Algorithm using Sequential Kalman Filter vol.21, pp.1, 2015, https://doi.org/10.5302/J.ICROS.2015.14.9053
  2. Dynamic Object Tracking of a Quad-rotor with Image Processing and an Extended Kalman Filter vol.21, pp.7, 2015, https://doi.org/10.5302/J.ICROS.2015.14.0138
  3. Real-Time Flight Testing for Developing an Autonomous Indoor Navigation System for a Multi-Rotor Flying Vehicle vol.40, pp.4, 2016, https://doi.org/10.3795/KSME-A.2016.40.4.343
  4. Formation Flight of Multiple UAVs via Onboard Sensor Information Sharing vol.15, pp.7, 2015, https://doi.org/10.3390/s150717397