Nao Robot Navigation System Structure Development in an Agent-Based Architecture of the RAPP Platform

  • Wojciech Dudek
  • Wojciech Szynkiewicz
  • Tomasz Winiarski
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 440)


This paper focuses on the development of a navigation system structure for the Nao humanoid robot in an agent-oriented distributed architecture. The proposed navigation system is a part of the RAPP framework, a cloud based robotics platform. The RAPP framework is an open-source software platform to support the creation and delivery of robotic applications, which are expected to increase the versatility and utility of robots. All navigation tasks are defined and divided into separate components. The robot navigation system consists of a relative localisation based on Extended Kalman Filter (EKF) using both IMU and odometry measurements, visual QR-code based global localization, path planning, and motion control components. A proper allocation of navigation components, in the four-agent structure of the RAPP platform, is the main goal of this work. Navigation system components are implemented using Robot Operating System and Nao robot programming framework—NAOqi. Experimental results for the Nao robot are presented to show the validity of the proposed approach.


Humanoid navigation Nao robot Agent system 



This work is funded by the FP7 Collaborative Project RAPP (Grant Agreement No. 610947), funded by the European Commission.


  1. 1.
    Winiarski, T., Banachowicz, K., Seredyński, D.: Multi-sensory feedback control in door approaching and opening. In: Intelligent Systems’2014. Advances in Intelligent Systems and Computing, vol. 323, pp. 57–70. Springer International Publishing (2015)Google Scholar
  2. 2.
    Psomopoulos, F., Tsardoulias, E., Giokas, A., Zieliński, C., Prunet, V., Trochidis, I., Daney, D., Serrano, M., Courtes, L., Arampatzis, S., Mitkas, P.: Rapp system architecture. In: IROS 2014—Assistance and Service Robotics in a Human Environment, Workshop in conjunction with IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, Illinois, Sept 14, pp. 14–18 (2014)Google Scholar
  3. 3.
    Zieliński, C., Szynkiewicz, W., Figat, M., Szlenk, M., Kornuta, T., Kasprzak, W., Stefańczyk, M., Zielińska, T., Figat, J.: Reconfigurable control architecture for exploratory robots. In: Kozńowski, K. (ed.) 10th International Workshop on Robot Motion and Control (RoMoCo), pp. 130–135. IEEE (2015)Google Scholar
  4. 4.
    Wei, C., Xu, J., Wang, C., Wiggers, P., Hindriks, K.: An approach to navigation for the humanoid robot nao in domestic environments. In: Towards Autonomous Robotic Systems, vol. 8069, pp. 298–310. Springer, Berlin (2014)Google Scholar
  5. 5.
    Figat, J., Kasprzak, W.: NAO-mark vs QR-code recognition by NAO robot vision. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds.) Progress in Automation, Robotics and Measuring Techniques. Vol. 2 Robotics. Advances in Intelligent Systems and Computing (AISC), vol. 351, pp. 55–64. Springer (2015)Google Scholar
  6. 6.
    Gouda, W., Gomaa, W., Ogawa, T.: Vision based slam for humanoid robots: a survey. In: 2013 Japan-Egypt International Conference on Electronics, Communications and Computers (JEC-ECC), pp. 170–175. IEEE (2013)Google Scholar
  7. 7.
    Faragasso, A., Oriolo, G., Paolillo, A., Vendittelli, M.: Vision-based corridor navigation for humanoid robots. In: 2013 IEEE International Conference Robotics and Automation (ICRA), pp. 3190–3195 (2013)Google Scholar
  8. 8.
    Wirbel, E., Bonnabel, S., Fortelle, A.D.L., Moutarde, F.: Humanoid robot navigation: getting localization information from vision. J. Intell. Syst. 23(2), 113–132 (2014)Google Scholar
  9. 9.
    Wen, S., Othman, K.K.M., Rad, A., Zhang, Y., Zhao, Y.: Indoor SLAM using laser and camera with closed-loop controller for NAO humanoid robot. Abstr. Appl. Anal. 2014, 8 p (2014)Google Scholar
  10. 10.
    Johannssen, F.: Nao in the cloud. Knowledge sharing for robots via cloud services. In: Workshop on Software Development and Integration in Robotics ICRA 2013 (2013)Google Scholar
  11. 11.
    Foundatioin, O.S.R.: Robot Operating System. [Online; Accessed 21-May-2015]
  12. 12.
    Zieliński, C., Winiarski, T.: Motion generation in the MRROC++ robot programming framework. Int. J. Robot. Res. 29(4), 386–413 (2010)CrossRefGoogle Scholar
  13. 13.
    Zieliński, C., Kornuta, T., Trojanek, P., Winiarski, T., Walcki, M.: Specification of a multi-agent robot-based reconfigurable fixture control system. Robot Motion and Control 2011 (Lecture Notes in Control and Information Sciences), vol. 422, pp. 171–182 (2012)Google Scholar
  14. 14.
    Zieliński, C., Winiarski, T.: General specification of multi-robot control system structures. Bull. Polish Acad. Sci.—Tech. Sci. 58(1), 15–28 (2010)Google Scholar
  15. 15. SysML documentation. (2003) [Online; Accessed 21-May-2015]
  16. 16.
    Moore, T., Stouch, D.: A Generalized Extended Kalman Filter Implementation for the Robot Operating System. [Online; Accessed 17-Sept-2015]
  17. 17.
    Marder-Eppstein, E., Berger, E., Foote, T., Gerkey, B., Konolige, K.: The office marathon: robust navigation in an indoor office environment. In: 2010 IEEE International Conference on Robotics and Automation (ICRA), pp. 300–307 (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Wojciech Dudek
    • 1
  • Wojciech Szynkiewicz
    • 1
  • Tomasz Winiarski
    • 1
  1. 1.Warsaw University of TechnologyWarsawPoland

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