DOI QR코드

DOI QR Code

A Study on Swarm Robot-Based Invader-Enclosing Technique on Multiple Distributed Object Environments

  • Ko, Kwang-Eun (School of Electrical and Electronics Engineering, Chung-Ang University) ;
  • Park, Seung-Min (School of Electrical and Electronics Engineering, Chung-Ang University) ;
  • Park, Jun-Heong (School of Electrical and Electronics Engineering, Chung-Ang University) ;
  • Sim, Kwee-Bo (School of Electrical and Electronics Engineering, Chung-Ang University)
  • 투고 : 2011.04.23
  • 심사 : 2011.06.14
  • 발행 : 2011.11.01

초록

Interest about social security has recently increased in favor of safety for infrastructure. In addition, advances in computer vision and pattern recognition research are leading to video-based surveillance systems with improved scene analysis capabilities. However, such video surveillance systems, which are controlled by human operators, cannot actively cope with dynamic and anomalous events, such as having an invader in the corporate, commercial, or public sectors. For this reason, intelligent surveillance systems are increasingly needed to provide active social security services. In this study, we propose a core technique for intelligent surveillance system that is based on swarm robot technology. We present techniques for invader enclosing using swarm robots based on multiple distributed object environment. The proposed methods are composed of three main stages: location estimation of the object, specified object tracking, and decision of the cooperative behavior of the swarm robots. By using particle filter, object tracking and location estimation procedures are performed and a specified enclosing point for the swarm robots is located on the interactive positions in their coordinate system. Furthermore, the cooperative behaviors of the swarm robots are determined via the result of path navigation based on the combination of potential field and wall-following methods. The results of each stage are combined into the swarm robot-based invader-enclosing technique on multiple distributed object environments. Finally, several simulation results are provided to further discuss and verify the accuracy and effectiveness of the proposed techniques.

키워드

참고문헌

  1. H. Yamaguchi, "A Cooperative Hunting Behavior by Mobile Robot Troops," International Journal of Robotics Research, vol. 18, no. 9, pp. 931-940, 1999 https://doi.org/10.1177/02783649922066664
  2. D. J. Park and B. E. Mullins, "Toward Finding an Universal Search Algorithm for Swarm Robots," in Proceedings of 2003 IEEE/RSJ Int. Conference on Intelligent Robots and Systems, pp. 1945-1950, 2003
  3. K. Sugawara, I. Yoshihara, K. Abe and M. Sano, "Cooperative behavior of interacting robots," Artificial Life and Robotics, vol. 2, no. 2, pp. 62-67, 1998 https://doi.org/10.1007/BF02471156
  4. G. Welch, G. Bishop, "An Introduction to the Kalman Filter," UNC-Chapel Hill, TR 95-041, July 24, 2006
  5. S. J. Julier, J. K. Uhlmann, "A New Extension of the Kalman Filter to Nonlinear Systems," in Proceedings of AeroSense: 11th Int. Symp. Aerospace/Defense Sensing, Simulation and Controls, pp. 182-193, 1997
  6. E. A. Wan and R. Van der Merwe, "The Unscented Kalman Filter for Nonlinear Estimation," in Proceddings of Symp. Adaptive Syst. Signal Process., Commun. Contr., pp. 153-158, 2000
  7. M. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, "A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking," IEEE Transactions on Signal Processing, vol. 50, no. 2, 2002
  8. G. Sun, J. Chen, and W. Guo, "Single Processing Techniques in Network-aided Positioning," IEEE Signal Proc. Magazine, vol. 22, no. 4, pp. 24-40, 2005 https://doi.org/10.1109/MSP.2005.1458275
  9. Yousief, M. Horus, "A WLAN-based indoor location determination system," Ph.D thesis, Univ. of Maryland at College Park, 2004
  10. Y. Lin, I. Jan, P. Ko, Y. Chen, J. Wong, G. Jan, "A Wireless PDA-based Physiological Monitoring System for Patient Transport," IEEE Transactions on IT in Biomedicine, vol. 8, no. 4, pp. 439-447, 2004 https://doi.org/10.1109/TITB.2004.837829
  11. F. Gustafsson and F. Gunnarsson, "Mobile Positioning Using Wireless Networks", IEEE Signal Proc. Magazine, vol. 22, no. 4, pp. 41-53, 2005 https://doi.org/10.1109/MSP.2005.1458284
  12. Marco Crepaldi, Analysis, design and simulation of an UWB receiver for indoor localization, Dissertation, Politecnico Di Torino, 2005.
  13. J. S, Kim, F. Allgower, "A Nonlinear Synchronization Scheme for Hindmarsh-Rose Models," Journal of Electrical Engineering & Technology, vol. 5, no. 1, pp. 163-170, 2010 https://doi.org/10.5370/JEET.2010.5.1.163
  14. D. Koller, J. Weber, and J. Malik, "Robust Multiple Car Tracking with Occlusion Reasoning," in Proceedings of the 3rd European conference on Computer Vision, vol. 1, pp.189-199, 1994.
  15. S. Gezici, Z. Tian, G. B. Giannakis, H. Ko-bayashi, A.F. Molisch, H. Vincent Poor, and Z. Sahinoglu, "Localization via Ultra-Wideband Radios," IEEE Signal Proc. Magazine, vol. 22, no. 4, pp. 70-84, 2005
  16. A. H. Sayed, A. Tarighat, and N. Kha-jehnouri, "Networked-based Wireless Networks," IEEE Signal Proc. Magazine, Vol. 22, No. 4, pp. 24-40, 2005 https://doi.org/10.1109/MSP.2005.1458275
  17. A. Doucet, J. F. G. de Freitas, and N. J. Gordon, editors. "Sequential Monte Carlo Methods in Practice," Springer, New York, 2001
  18. Sangoh Jeong, "Histogram-Based Color Image Retrieval", Psych221/EE362 Project Report, 2001
  19. J. Borenstein, Y. Koren, "Potential Field Methods and Their Inherent Limitations for Mobile Robot Navigation", in Proceeding of the IEEE International Conference on Robotics and Automation, California, April 1991
  20. L. C. A. Pimenta and A. R. Fonseca, "Robot Navigation Based on Electrostatic Field Computation", IEEE Transaction on Magnetics, vol. 42, no. 4, 2006
  21. J. Ren, K. A. McIsaac and R. V. Patel, "Modified Newton's Method Applied to Potential Field-Based Navigation for Mobile Robots", IEEE Transaction on Robotics, vol. 22, no. 2, 2006
  22. R. Daily, D. M. Bevly, "Harmonic Potential Field Path Planning for High Speed Vehicles", American Control Conference 2008, Seattle, USA, June 11-13 2008
  23. S. Yannier, A. Onat, A. sabanovic, "Basic Configuration for Mobile Robots", in Proceeding of International Conference on Industrial Technology, vol. 1, pp. 256-261, Maribor, Slovenia, 2003
  24. Y. Li and S. Li, "Particle Filtering for Range-Based Localization in Wireless Sensor Networks," in Proceedings of the 7th World Congress on Intelligent Control and Automation, Chongqing, China, June 25-27, 2008
  25. E. S-. Navarro, V. Vivekananda, V. W. S. Wong, "Dual and Mixture Monte Carlo Localization Algorithms for Mobile Wireless Sensor Networks," IEEE Wireless Communications and Networking Conference, Hong Kong, March 11-15 2007
  26. M. Rudafshani and S. Datta, "Localization in Wireless Sensor Networks", in Proceedings of the 6th International Conference on Information Processing in Sensor Networks, Cambridge, Massachusetts, April, 25-27, 2007
  27. Madow, "On the theory of systematic sampling II," Annals of Mathematical Statistics, pp. 333-354, 1949
  28. J. Mclurkin, "Multi-Robot Systems Engineering," Rice University, Department of Computer Science, URL=