Science in China Series F: Information Sciences

, Volume 50, Issue 5, pp 697–710 | Cite as

Center-configuration selection technique for the reconfigurable modular robot

  • Liu JinGuo 
  • Wang YueChao 
  • Li Bin 
  • Ma ShuGen 
  • Tan DaLong 
Article

Abstract

The reconfigurable modular robot has an enormous amount of configurations to adapt to various environments and tasks. It greatly increases the complexity of configuration research in that the possible configuration number of the reconfigurable modular robot grows exponentially with the increase of module number. Being the initial configuration or the basic configuration of the reconfigurable robot, the center-configuration plays a crucial role in system’s actual applications. In this paper, a novel center-configuration selection technique has been proposed for reconfigurable modular robots. Based on the similarities between configurations’ transformation and graph theory, configuration network has been applied in the modeling and analyzing of these configurations. Configuration adjacency matrix, reconfirmation cost matrix, and center-configuration coefficient have been defined for the configuration network correspondingly. Being similar to the center-location problem, the center configuration has been selected according to the largest center-configuration coefficient. As an example of the reconfigurable robotic system, AMOEBA-I, a three-module reconfigurable robot with nine configurations which was developed in Shenyang Institute of Automation (SIA), Chinese Academy of Sciences (CAS), has been introduced briefly. According to the numerical simulation result, the center-configuration coefficients for these nine configurations have been calculated and compared to validate this technique. Lastly, a center-configuration selection example is provided with consideration of the adjacent configurations. The center-configuration selection technique proposed in this paper is also available to other reconfigurable modular robots.

Keywords

reconfigurable robot modular robot center-configuration configuration network reconfiguration cost matrix center-configuration coefficient 

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References

  1. 1.
    Zykov V, Mytilinaios E, Adams B, et al. Self-reproducing machines. Nature, 2005, 435(7038): 163–164CrossRefGoogle Scholar
  2. 2.
    Mackenzie D. Shape shifters tread a daunting path toward reality. Science, 2003, 301(5634): 754–756CrossRefGoogle Scholar
  3. 3.
    Polymorphic Robotics Laboratory [OL][2006-05-1]. http://www.isi.edu/robots
  4. 4.
    Shen W M, Salemi B, Will P. Hormone-inspired adaptive communication and distributed control for CONRO self-reconfigurable robots. IEEE Trans Robot Automat, 2002, 18(5): 700–712CrossRefGoogle Scholar
  5. 5.
    Støy K, Shen W M, Will P. Using role based control to produce locomotion in chain-type self-reconfigurable robot. IEEE/ASME Trans Mech, 2002, 7(4): 410–417CrossRefGoogle Scholar
  6. 6.
    Modular robotics at PARC[OL].[2006-05-1]. http://www2.parc.com/spl/projects/modrobots/
  7. 7.
    Yim M. A reconfigurable modular robot with many modes of locomotion. In: Proc of the JSME Int Conf on Advanced Mechatronics, 1993. 283–288Google Scholar
  8. 8.
    Yim M, Duff D, Roufas K. Polybot: a modular reconfigurable robot. In: Proc of IEEE Int Conf on Robotics and Automation, 2000. 514–520Google Scholar
  9. 9.
    Paredis C J, Brown H B, Khosla P K. A rapidly deployable manipulator system. Robot Auton Syst, 1997, 21(3): 289–304CrossRefGoogle Scholar
  10. 10.
    Ünsal C, Khosla P. A multi-layered planner for self-reconfiguration of a uniform group of I-cube modules. In: Proc of IEEE/RSJ Int Conf on Intelligent Robots and Systems, 2001. 598–605Google Scholar
  11. 11.
    Distributed Modular Robotic Systems [OL][2006-05-1]. http://unit.aist.go.jp/is/dsysd/research.htm
  12. 12.
    Yoshida E, Murata S, Kamimura A, et al. A self-reconfigurable modular robot: reconfiguration planning and experiments. I Int J Robot Res, 2002, 21(10): 903–916CrossRefGoogle Scholar
  13. 13.
    Yoshida E, Murata S, Kamimura A, et al. Evolutionary synthesis of dynamic motion and reconfiguration process for a modular robot M-TRAN. In: Proc of IEEE Int Symposium on Computational Intelligence in Robotics and Automation, 2003. 1004–1010Google Scholar
  14. 14.
    Kamimura A, Kurokawa H, Yoshida E, et al. Automatic locomotion design and experiments for a modular robotic system. IEEE/ASME Trans Mech, 2005, 10(3): 314–325CrossRefGoogle Scholar
  15. 15.
    Fukuda T, Nakagawa S. Dynamically reconfigurable robot system. In: Proc of IEEE Int Conf on Robotics and Automation, 1988. 1581–1586Google Scholar
  16. 16.
    Rus D, Vona M. Crystalline robots: self-reconfiguration with compressible unit modules. Auton Robot, 2001, 10(1): 107–124MATHCrossRefGoogle Scholar
  17. 17.
    Kotay K, Rus D, Vona M, et al. The self-reconfiguring robotic molecule. In: Proc of IEEE Int Conf on Robotics and Automation, 1998. 424–431Google Scholar
  18. 18.
    Fei Y Q, Zhao X F. Modules classification and automatic generation of kinematics on self-reconfigurable modular machines. J Intell Robot Syst, 2005, 43(2–4): 147–159CrossRefGoogle Scholar
  19. 19.
    Xu W, Wang S G, Wang A L. Towards an efficient self-organizing reconfiguration method for self-reconfigurable robots. J Intell Robot Syst, 2003, 37(4): 415–425CrossRefGoogle Scholar
  20. 20.
    Wu Q X, Cao G Y, Fei Y Q. Motion simulation and experiment of a novel modular self-reconfigurable robot. J Southeast Univ, 2006, 22(2): 185–190Google Scholar
  21. 21.
    Liu J G, Wang Y C, Li B, et al. Link-type shape shifting modular robot for search and rescue. High Tech Lett, 2004, 10(Supp): 179–183Google Scholar
  22. 22.
    Liu J G, Wang Y C, Li B, et al. Representing and enumerating of the non-isomorphic configurations of a shape shifting modular robot. Chinese J Mech Engin (in Chinese), 2006, 42(1): 98–105Google Scholar
  23. 23.
    Liu J G, Wang Y C, Ma S G, et al. Analysis of tipover stability for novel shape shifting modular robot. Chinese J Mech Engin, 2006, 19(2): 187–192CrossRefGoogle Scholar
  24. 24.
    Liu J G, Ma S G, Lu Z L, et al. Design and experiment of a novel link-type shape shifting modular robot series. In: Proc of IEEE Int Conf on Robotics and Biomimetics, 2005. 318–323Google Scholar
  25. 25.
    Liu J G, Wang Y C, Li B, et al. Transformation technique research of the improved link-type shape shifting modular robot. In: Proc of IEEE Int Conf on Mechatronics and Automation, 2006. 295–300Google Scholar
  26. 26.
    Li B, Wang Y C, Liu J G, et al. A novel shape shifting tracked mobile mechanism. Chinese Innovation Patent, 200420012106.9, 2004-03-31Google Scholar
  27. 27.
    Wang T M, Zou D, Chen D S. Mechanism design and control method of reconfigurable tracked robot. J Beijing Univ Aeronaut Astronaut (in Chinese), 2005, 31(7): 705–708Google Scholar
  28. 28.
    Yu H B, Yu J J, Bi S S, et al. Configuration synthesis of reconfigurable robot based on graph theory. Chinese J Mech Engin (in Chinese), 2005, 41(8): 79–83Google Scholar
  29. 29.
    Wei Y H, Zhao J, Cai H G. Task-based method for determining topology of reconfigurable modular robot. Chinese J Mech Engin (in Chinese), 2006, 42(B05): 93–97Google Scholar
  30. 30.
    Li M T, Huang B, Liu G C, et al. A modular reconfigurable tracked micro-robot. Robot (in Chinese), 2006, 28(5): 548–552Google Scholar
  31. 31.
    Zheng H J, Wang J S, Li T M. Reconfigurable robot unit structure design and assembly character analyses. Chinese J Mech Engin (in Chinese), 2003, 39(7): 34–37Google Scholar
  32. 32.
    Chen I M, Burdick J W. Enumerating the non-isomorphic assembly configuration of modular robotic systems. In: Proc. of IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 1993. 1985–1992Google Scholar
  33. 33.
    Castano A, Will P. Representing and discovering the configuration of CONRO Robots. In: Proc. of IEEE Int. Conf. on Robotics and Automation, 2001. 3503–3509Google Scholar
  34. 34.
    Bi Z M, Zhang W J. Concurrent optimal design of modular robotic configuration. J Robot Syst, 2001, 18(2): 77–87MATHCrossRefGoogle Scholar
  35. 35.
    Yim M, Goldberg D, Casal A. Connectivity planning for closed-chain reconfiguration. In: Proc of SPIE 4196, Sensor Fusion and Decentralized Control in Robotic Systems III, 2000. 402–412Google Scholar
  36. 36.
    Chen I M. Theory and applications of modular reconfigurable robotic systems. Dissertation for the Doctoral Degree. California: California Institute of Technology, 1994Google Scholar
  37. 37.
    Butler Z, Kotay K, Rus D. Generic decentralized locomotion control for lattice-based self-reconfigurable robots. I Int J Robot Res, 2004, 23(9): 919–938CrossRefGoogle Scholar
  38. 38.
    Lu K C. Graph Theory and Its Application (in Chinese). Beijing: Tsinghua University Press, 1981Google Scholar
  39. 39.
    Jungnickel D. Graphs, Networks and Algorithms. Berlin, Heidelberg: Springer-Verlag, 1999Google Scholar
  40. 40.
    Minieka E. Optimization Algorithms for Network and Graphs (translated in Chinese by Li J Y, Zhao G Q). Beijing: China Railway Press, 1984Google Scholar
  41. 41.
    Yang F M, Hua G W, Deng M, et al. Some advances of the researches on location problems. Oper Res Manag Sci (in Chinese), 2005, 14(6): 1–7Google Scholar
  42. 42.
    Foul A. A 1-center problem on the plane with uniformly distributed demand points. Oper Res Lett, 2006, 34: 264–268MATHCrossRefMathSciNetGoogle Scholar
  43. 43.
    Pan S, Li X. An efficient algorithm for the euclidean r-centrum location problem. Appl Math Comput, 2005, 167(1): 716–728CrossRefMathSciNetGoogle Scholar
  44. 44.
    Wuchty S, Stadle P F. Centers of complex networks. J Theor Biol, 2003, 223(1): 45–53CrossRefGoogle Scholar
  45. 45.
    COSMOSMotion™ provides the following features and benefits [OL][2006-05-1]. http://www.solidworks.com/pages/products/cosmos/cosmosmotion/cmfeatures.html

Copyright information

© Science in China Press 2007

Authors and Affiliations

  • Liu JinGuo 
    • 1
    • 2
  • Wang YueChao 
    • 1
  • Li Bin 
    • 1
  • Ma ShuGen 
    • 1
    • 3
  • Tan DaLong 
    • 1
  1. 1.Robotics Laboratory of Chinese Academy of SciencesShenyang Institute of AutomationShenyangChina
  2. 2.COE Research InstituteRitsumeikan UniversityShiga-kenJapan
  3. 3.Graduate School of Chinese Academy of SciencesBeijingChina

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