DOI QR코드

DOI QR Code

Formation Algorithm with Local Minimum Escape for Unicycle Robots

유니사이클 로봇을 위한 지역최소점 탈출을 갖춘 포메이션 알고리즘

  • Received : 2012.11.28
  • Accepted : 2013.03.25
  • Published : 2013.04.01

Abstract

This paper presents formation control based on potential functions for unicycle robots. The unicycle robots move to formation position which is made from a reference point and neighboring robots. In the framework, a local minimum case occurred by combination of potential repulsed from neighboring robots and potential attracted from a formation line is presented, in which the robot escapes from a local minimum using a virtual escape point after recognizing trapped situation. As well, in the paper, potential functions are designed to keep the same distance between neighboring robots on a formation line, i.e. the relative distance between neighboring robots on a formation line is controlled by a potential function parameter. The simulation results show that the proposed approach can effectively construct straight line, V, and polygon formation for multiple robots.

Keywords

References

  1. D. H. Kim, "Self-organization of unicycle swarm robots based on a modified particle swarm framework," International Journal of Control, Automation and Systems, vol. 8, no. 3, pp. 622-629, Jun. 2010. https://doi.org/10.1007/s12555-010-0315-4
  2. M.-A. Fields, E. Haas, S. Hill, C. Stachowiak, and L. Barnes, "Effective robot team control methodologies for battlefield applications," International Conference on Intelligent Robots and Systems, pp. 5862-5867, 2009.
  3. J. S. Kim and Y. H. Joo, "Asynchronous behavior control algorithm of the swarm robot for surrounding intruders," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 18, no. 9, pp. 812-818, 2012. https://doi.org/10.5302/J.ICROS.2012.18.9.812
  4. T. Schmickl and K. Crailsheim, "Trophallaxis among swarm-robots: A biologically inspired strategy for swarm robotics," International Conference on Biomedical Robotics and Biomechatronics, pp. 377-382, 2006.
  5. M. N. Soorki, H. A. Talebi, and S. K. Y. Nikravesh, "A leader-following formation control of multiple mobile robots with active obstacle avoidance," 2011 19th Iranian Conference on Electrical Engineering, pp. 1-6, 2011.
  6. A. Marjovi, J. Nunes, P. Sousa, R. Faria, and L. Marques, "An olfactory-based robot swarm navigation method," IEEE International Conference on Robotics and Automation, pp. 4958-4963, 2010.
  7. M. H. Tak and Y. H. Joo, "Localization for cooperative behavior of swarm robots based on wireless sensor network," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 18, no. 8, pp. 725-730, 2012. https://doi.org/10.5302/J.ICROS.2012.18.8.725
  8. R. W. Beard, J. Lawton, and F. Y. Hadaegh, "A coordination architecture for spacecraft formation control," IEEE Transactions on Control Systems Technology, vol. 9, no. 6, pp. 777-790, 2001. https://doi.org/10.1109/87.960341
  9. H. Xu, H. Guan, A. Liang, and X. Yan, "A multi-robot pattern formation algorithm based on distributed swarm intelligence," 2010 Second International Conference on Computer Engineering and Applications, vol. 1, pp. 71-75, 2010.
  10. D. H. Kim, H. O. Wang, and S. Shin, "Decentralized control of autonomous swarm systems using artificial potential functions : Analytical design guidelines," Int. Journal of Intelligent and Robotic Systems, vol. 45, no. 4, pp. 369-394, 2006. https://doi.org/10.1007/s10846-006-9050-8
  11. B. Ranjbar-Sahraei, F. Shabaninia, A. Nemati, and S. D. Stan, "A novel robust decentralized adaptive fuzzy control for swarm formation of multiagent systems," IEEE Transactions on Industrial Electronics, vol. 59, no. 8, pp. 3124-3134, 2012.
  12. K. H. Kowdiki, R. K. Barai, and S. Bhattachary a, "Leader-follower formation control using artificial potential functions: A kinematic approach," International Conference on Advances in Engineering, Science and Management, pp. 500-505, 2012.
  13. V. T. L. Rampinelli, A. S. Brandão, M. Sarcinelli-Filho, F. N. Martinsy, and R. Carelliz, "Embedding obstacle avoidance in the control of a flexible multi-robot formation," 2010 IEEE International Symposium on Industrial Electro Nics, pp. 1846-1851, 2010.
  14. R. Haghighi and C. C. Chien, "Asynchronous dynamic multi-group formation for swarm robots," Decision and Control and European Control Conference, pp. 2744-2749, 2011.
  15. T. Eren, W. Whiteley, B. D. O. Anderson, A. S. Morse, and P. N. Belhumeur, "Information structures to secure control of rigid formations with leaderfollower architecture," Proc. of the American Control Conference, vol. 4, pp. 2966-2971, 2005.
  16. C. Lei and W. Yongji, "Robotics and vision conference," Robotics and Vision Conference, vol. 1, pp. 729-734, 2004.
  17. A. R. Pourshoghi and H. A. Talebi, "A new distributed coverage algorithm based on hexagonal formation," IEEE International Conference on Systems, pp. 740-744, 2009.
  18. F. Rivard, J. Bisson, and D. Letourneau, "Ultrasonic relative positioning for multi-robot systems," IEEE International Conference on Robotics and Automation, pp. 323-328, 2008.
  19. S. H. Kim, G. Lee, I. P. Hong, Y. J. J. Kim, and D. Y. Y. Kim, "New potential function for multi robot path planning : SWARM or SPREAD," The 2nd International Conference on Computer and Automation Engineering (ICCAE), pp. 557-561, 2010.
  20. S. S. Ge, C. H. Fua, and W. M. Liew, "Swarm formations using the general formation potential function," IEEE Conference on Robotics, Automati on and Mechatronics, vol. 2, pp. 655-660, 2004.
  21. M. Egerstedt and X. Hu, "A hybrid control approach to action coordination for mobile robots," Automatica, vol. 38, no. 1, pp. 125-130, 2002. https://doi.org/10.1016/S0005-1098(01)00185-6
  22. M. Egerstedt and X. Hu, "Formation constrained multiagent control," IEEE Transaction on Robotics and Automation, vol. 17, pp. 947-951, 2001. https://doi.org/10.1109/70.976029
  23. H. Jung, Y. Kim, and D. H. Kim, "Visual cooperation based on LOS for self-organization of swarm robots," International Journal of Control, Automation, and System, vol. 2, no. 1, pp. 216-224, Feb. 2013.
  24. Q. Zhu, Y. Yan, and Z. Xing, "Robot path planning based on artificial potential field approach with simulated annealing," International Conference on Intelligent Systems Design and Applications, IEEE Computer Society, pp. 622-627, 2006.
  25. L. R. Burden and J. D. Faires, Numerical Analysis, 9th Ed., Thomson Learning, 2010.

Cited by

  1. Potential-function-based shape formation in swarm simulation vol.12, pp.2, 2014, https://doi.org/10.1007/s12555-013-0133-6
  2. Implementation of symmetrical rank based formation for multiple robots vol.14, pp.1, 2016, https://doi.org/10.1007/s12555-014-0322-y