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CloudThinking as an Intelligent Infrastructure for Mobile Robotics

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Abstract

Mobile robotics is a transforming field that presents a varying set of challenges. The discussion on the autonomy of (self-powered) robots is not settled, and as the communication infrastructure evolves, centralized concepts become more attractive over distributed concepts. This paper presents the CloudThinking architecture applied to intelligent cloud-based robotic operation. CloudThinking offloads most of complex robotic tasks to a central cloud, which retrieves inputs from the environment as a whole in order to instruct the robots to perform its actions. CloudThinking is a natural approach to the orchestration of multiple specialized robotic systems, defining the best mechanisms for reaching a goal. Furthermore, this architecture provides a set of automatic features which can be useful for application developers. These features can fully exploit novel cloud tools development as it becomes available, providing a time-resilient infrastructure of easy upgrade. The resulting approach has the potential to create a different set of market for robotic application developers.

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Notes

  1. Strictly speaking, the rules of robotic soccer require such autonomous architectures, regardless of technical feasibility.

References

  1. Thrun, S. (2010). What we’re driving at. Official Blog, Google, October 9, 2010. http://googleblog.blogspot.com/2010/10/what-were-driving-at.html. Accessed Apr 18, 2013.

  2. Arumugam, S., Kalle, R. K., & Prasad, A. R. (2013). Wireless robotics: Opportunities and challenges. Wireless Personal Communications, 70(3), 1033–1058.

    Article  Google Scholar 

  3. Sadeghi, R., Barraca, J. P., & Aguiar, R. L. (2013). Collaborative relaying strategies in autonomic management of mobile robotics. Wireless Personal Communications, 70(3), 1077–1096. doi:10.1007/s11277-013-1104-1.

    Article  Google Scholar 

  4. Şahin, E. (2005). Swarm robotics: From sources of inspiration to domains of application. Swarm Robotics, Lecture Notes in Computer Science, 3342, 10–20.

    Article  Google Scholar 

  5. Nehmzow, U. (1993). Mobile robotics: A practical introduction. Berlin: Springer.

    Google Scholar 

  6. Almeida, L., Santos, F., Facchinetti, T., Pedreiras, P., Silva, V., & Lopes, L. S. (2004). Coordinating distributed autonomous agents with a real-time database: The CAMBADA project. In Computer and Information Sciences-ISCIS 2004 (pp. 876–886), Berlin: Springer.

  7. Horn, P. (2001). Autonomic computing: IBM’s perspective on the state of information technology. IBM technical report.

  8. IBM. (2003). An architectural blueprint for autonomic computing. IBM technical report.

  9. Gudgin, M., Hadley, M., Mendelsohn, N., Moreau, J.-J., Nielsen, H. F., Karmarkar, A., & Lafon, Y., (Eds.). (2007). SOAP version 1.2 part 1: Messaging framework (2nd ed.). World Wide Web Consortium, 27 April.

  10. Fielding, R. T. (2000). Architectural styles and the design of network-based software architectures. Ph.D. Dissertation, chapter 5, University of California, Irvine, AAI9980887.

  11. Object Management Group. Common object request broker architecture. Object Management Group Standard. http://www.omg.org/spec/

  12. Shin, S.-O., Lee, J.-O., & Baik, D.-K. (2007). A mobile agent-based multi-robot design method for high-assurance. In High assurance systems engineering symposium, 2007. HASE ’07. 10th IEEE (pp. 389–390).

  13. Darche, P., Raverdy, P.-G., & Commelin, E. (1995). ActNet: The actor model applied to mobile robotic environments. In OBPDC 1995 (pp. 273–289).

  14. Mohan, Y., & Ponnambalam, S.G. (2009). An extensive review of research in swarm robotics. In World Congress on nature and biologically inspired computing. NaBIC 2009 (pp. 140–145).

  15. Han, Q., Wang, Q., Zhu, X., & Xu, J. (2011). Path planning of mobile robot based on improved ant colony algorithm. In 2011 international conference on consumer electronics, communications and networks (CECNet) (pp. 531–533).

  16. Kuffner, J. J. (2010). Cloud-enabled robots. In IEEE-RAS international conference on humanoid robotics. Nashville, TN.

  17. Goldberg, K. (2013). Cloud robotics. Retrieved July 2013. http://goldberg.berkeley.edu/cloud-robotics/.

  18. Dean, J., & Ghemawat, S. (2008). MapReduce: Simplified data processing on large clusters. Communications of the ACM, 51, 107–113.

    Article  Google Scholar 

  19. Quigley, M., Gerkey, B., Conley, K., Faust, J., Foote, T., Leibs, J., Rob, W., & Ng, A. Y. (2009). ROS: An open-source Robot Operating System. ICRA Workshop on Open Source Software, 3(3.2)

  20. Dang, H., & Allen, P. (2012). Learning grasp stability. In 2011 IEEE international conference on robotics and automation (ICRA) (pp. 2392–2397). IEEE.

  21. Gostai (2013). GostaiNet. www.gostai.com/activities/consumer.

  22. Arumugam, R., Enti, V., Bingbing, L., Xiaojun, W., Baskaran, K., Kong, A. F. F., et al. (2011). DAvinCi: A cloud computing framework for service robots. In IEEE international conference on robotics and automation (ICRA) (pp. 3084–3089).

  23. Waibel, M., Beetz, M., Civera, J., d’Andrea, J., Elfring, J., Galvez-Lopez, D., et al. (2011). RoboEarth—a World Wide Web for robots. IEEE Robotics and Automation Magazine, 18, 69–82.

    Article  Google Scholar 

  24. Hunziker, D., Gajamohan, M., Waibel, M., & D’Andrea, R. (2013). Rapyuta: The RoboEarth cloud engine. In Proceedings IEEE international conference on robotics and automation (ICRA) (pp. 438–444). Karlsruhe, Germany.

  25. Anderson, T., Peterson, L., Shenker, S., & Turner, J. (2005). Overcoming the internet impasse through virtualization. Computer, 38(4), 34–41.

    Article  Google Scholar 

  26. McKeown, N., et al. (2008). OpenFlow: Enabling innovation in campus networks. ACM SIGCOMM Computer Communication Review, 38(2), 69–74.

    Article  Google Scholar 

  27. Jones, J. L. (2006). Robots at the tipping point: The road to iRobot Roomba. IEEE on Robotics and Automation Magazine, 13(1), 76–78.

    Article  Google Scholar 

  28. Malehorn, K., Liu, W., Im, H., Bzura, C., Padir, T., & Tulu, B. (2012). The emerging role of robotics in home health care. AMCIS 2012 Proceedings, Paper 62.

  29. Moradi, H., Kawamura, K., Prassler, E., Muscato, G., Fiorini, P., et al. (2013). Service robotics (the rise and bloom of service robots). IEEE on Robotics and Automation Magazine, 20(3), 22–24.

    Article  Google Scholar 

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Acknowledgments

This work was supported by project Cloud Thinking (CENTRO-07-ST24-FEDER-002031), co-funded by QREN, “Mais Centro” program.

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Correspondence to Rui L. Aguiar.

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Aguiar, R.L., Gomes, D., Barraca, J.P. et al. CloudThinking as an Intelligent Infrastructure for Mobile Robotics. Wireless Pers Commun 76, 231–244 (2014). https://doi.org/10.1007/s11277-014-1687-1

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