Advertisement

Ubiquitous Robot: A New Paradigm for Intelligence

  • Tiantian Zhang
  • Bo Yuan
  • Tao Meng
  • Yinghao Ren
  • Houde Liu
  • Xueqian Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9937)

Abstract

This paper presents a systematic review of the recent development in ubiquitous robotics, with a focus on its implication on intelligence. Ubiquitous robot (Ubibot), the third generation robot, is characterized by its unprecedented power to sense environments and provide sophisticated services autonomously. Based on the architectures of existing Ubibot projects, we describe a general framework containing the perception, intelligence and execution modules as well as the middleware layer used to integrate the three modules to make them collaborate seamlessly. Two representative projects are introduced to exemplify the state-of-the-art progress in Ubibot, along with a brief discussion of various underlying communication techniques. In the perspective of intelligence, we point out that Ubibot opens up new horizons for investigating and applying popular AI techniques such as computer vision and pattern recognition, compared to traditional robots. Furthermore, a list of new challenging research topics is identified that deserve full consideration in the future to make Ubibot more robust, effective and adaptive.

Keywords

Ubiquitous robot Middleware Intelligence Communication 

Notes

Acknowledgement

This work was supported by the 863 Program (No. 2015AAXX46201), Natural Science Foundation of Guangdong Province (No. 2015A030313881) and Research Foundation of Shenzhen (No. JCYJ20140509172959962).

References

  1. 1.
    Kim, J.H., Lee, K.H., Kim, Y.D., Kuppuswamy, N.S., Jo, J.: Ubiquitous robot: a new paradigm for integrated services. In: Proceedings of 2007 IEEE International Conference on Robotics and Automation, pp. 2853–2858 (2007)Google Scholar
  2. 2.
    Kim, Y.D., Kim, Y.J., Kim, J.H., Lim, J.R.: Implementation of artificial creature based on interactive learning. In: Proceedings of the FIRA Robot World Congress, pp. 369–373 (2002)Google Scholar
  3. 3.
  4. 4.
    Nakamura, Y., Machino, T., Motegi, M., Iwata, Y., Miyamoto, T., Iwaki, S., Muto, S., Shimokura, K.I.: Framework and service allocation for network robot platform and execution of interdependent services. Robot. Auton. Syst. 56(10), 831–843 (2008)CrossRefGoogle Scholar
  5. 5.
    Kim, J.H.: Ubiquitous robot. In: Reusch, B. (ed.) Computational Intelligence, Theory and Applications. Advances in Soft Computing, vol. 33, pp. 451–459. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  6. 6.
    Kim, J.H.: Ubiquitous robot: recent progress and development. In: Proceedings of SICE-ICASE International Joint Conference, pp. I-25–I-30. IEEE (2006)Google Scholar
  7. 7.
    Sanfeliu, A., Hagita, N., Saffiotti, A.: Network robot systems. Robot. Auton. Syst. 56(10), 793–797 (2008)CrossRefGoogle Scholar
  8. 8.
  9. 9.
    Brady, M.: Artificial intelligence and robotics. Artif. Intell. 26(1), 79–121 (1985)CrossRefGoogle Scholar
  10. 10.
    Gigras, Y., Gupta, K.: Ambient intelligence in ubiquitous robotics. Int. J. Comput. Sci. Inf. Technol. 2(4), 1438–1440 (2011)Google Scholar
  11. 11.
    Kim, J.H., Kim, Y.D., Lee, K.H.: The third generation of robotics: ubiquitous robot. In: Proceedings of the 2nd International Conference on Autonomous Robots and Agents (2004)Google Scholar
  12. 12.
    Kim, B.K., Tomokuni, N., Ohara, K., Tanikawa, T., Ohba, K., Hirai, S.: Ubiquitous localization and mapping for robots with ambient intelligence. In: Proceedings of 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4809–4814. IEEE (2006)Google Scholar
  13. 13.
    Do, H.M., Kim, B.K., Kim, Y.S., Lee, J.H., Ohara, K., Sugawara, T., Tomizawa, T., Liang, X., Tanikawa, T., Ohba, K.: Development of simulation framework for ubiquitous robots using RT-middleware. In: Proceedings of International Conference on Control, Automation and Systems, pp. 2483–2486. IEEE (2007)Google Scholar
  14. 14.
    Saffiotti, A., Broxvall, M., Gritti, M., LeBlanc, K., Lundh, R., Rashid, J., Seo, B.S., Cho, Y.J.: The PEIS-ecology project: vision and results. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2329–2335. IEEE (2008)Google Scholar
  15. 15.
    Ha, Y.G., Sohn, J.C., Cho, Y.J., Yoon, H.: A robotic service framework supporting automated integration of ubiquitous sensors and devices. Inf. Sci. 177(3), 657–679 (2007)CrossRefGoogle Scholar
  16. 16.
    Ha, Y.G., Sohn, J.C., Cho, Y.J., Yoon, H.: Towards a ubiquitous robotic companion: design and implementation of ubiquitous robotic service framework. ETRI J. 27(6), 666–676 (2005)CrossRefGoogle Scholar
  17. 17.
    Jeong, I.B., Kim, J.H.: Multi-layered architecture of middleware for ubiquitous robot. In: Proceedings of 2008 IEEE International Conference on Systems, Man and Cybernetics. pp. 3479–3484. IEEE (2008)Google Scholar
  18. 18.
    Idachaba, I., Ike, D.U., Hope, O.: Future trends in fiber optics communication. In: Proceedings of the World Congress on Engineering, vol. 1 (2014)Google Scholar
  19. 19.
    Lee, J.S., Su, Y.W., Shen, C.C.: A comparative study of wireless protocols: Bluetooth, UWB, ZigBee, and Wi-Fi. In: Proceedings of the 33rd Annual Conference of the IEEE Industrial Electronics Society, pp. 46–51 (2007)Google Scholar
  20. 20.
    Porcino, D., Hirt, W.: Ultra-wideband radio technology: potential and challenges ahead. Commun. Mag. 41(7), 66–74 (2003)CrossRefGoogle Scholar
  21. 21.
    Akyildiz, I.A., Lee, W.Y., Vuran, M.C., Mohanty, S.: Next generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Comput. Netw. 50(13), 2127–2159 (2006)CrossRefzbMATHGoogle Scholar
  22. 22.
    Koening, S., Lopez-Diaz, D., Antes, J., Boes, F., Henneberger, R., Leuther, A., Tessmann, A., Schmogrow, R., Hillerkuss, D., Palmer, R., Zwick, T., Koos, C., Freude, W., Ambacher, O., Leuthold, J.: Wireless sub-THz communication system with high data rate. Nat. Photonics 7(12), 977–981 (2013)CrossRefGoogle Scholar
  23. 23.
    Yao, J., Chi, N., Yang, P., Cui, H., Wang, J., Li, J., Xu, D., Ding, X.: Study and outlook of terahertz communication technology. Chin. J. Lasers 36(9), 2213–2233 (2009)CrossRefGoogle Scholar
  24. 24.
    Duan, L.M., Lukin, M.D., Cirac, J.I., Zoller, P.: Long-distance quantum communication with atomic ensembles and linear optics. Nature 414(6862), 413–418 (2001)CrossRefGoogle Scholar
  25. 25.
    Akyildiz, I.F., Jornet, J.M., Han, C.: Terahertz band: next frontier for wireless communications. Phys. Commun. 12, 16–32 (2014)CrossRefGoogle Scholar
  26. 26.
    Park, S.C., Park, M.K., Kang, M.G.: Super-resolution image reconstruction: a technical overview. IEEE Signal Process. Mag. 20(3), 21–36 (2003)CrossRefGoogle Scholar
  27. 27.
    Arkin, E.M., Hassin, R.: Approximation algorithms for the geometric covering salesman problem. Discrete Appl. Math. 55, 197–218 (1994)MathSciNetCrossRefzbMATHGoogle Scholar
  28. 28.
    Yao, X., Higuchi, T.: Promises and challenges of evolvable hardware. IEEE Trans. Syst. Man Cybern. Part C 29(1), 87–97 (1999)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Tiantian Zhang
    • 1
  • Bo Yuan
    • 1
  • Tao Meng
    • 1
  • Yinghao Ren
    • 1
  • Houde Liu
    • 2
  • Xueqian Wang
    • 2
  1. 1.Intelligent Computing Lab, Division of Informatics, Graduate School at ShenzhenTsinghua UniversityShenzhenPeople’s Republic of China
  2. 2.Shenzhen Laboratory of Space Robotics and Telescience, Graduate School at ShenzhenTsinghua UniversityShenzhenPeople’s Republic of China

Personalised recommendations