Automated Drawing Recognition and Reproduction with a Multisensory Robotic Manipulation System

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


Article presents a multisensory robotic system, that is reproducing contour drawings. Initially the system detects a sheet of paper with a reference drawing, determines contours of the drawing, and then draws contour image on a blank sheet of paper. The reproduction conserves features of the original drawing—shapes, location and scale. The system was created with usage of an embodied agent theory. In this article two main parts of a designed system are presented—vision module (virtual receptor) and control subsystem. System is verified on a modified industrial manipulator acting as a service robot with an eye in hand camera and a force/torque sensor mounted in the wrist.


Service robot Controller design Sensor fusion 



This project was funded by the National Science Centre according to the decision number DEC-2012/05/D/ST6/03097.


  1. 1.
    Zieliński, C., Winiarski, T.: Motion generation in the MRROC++ robot programming framework. Int. J. Robot. Res. 29(4), 386–413 (2010)CrossRefGoogle Scholar
  2. 2.
    Winiarski, T., Banachowicz, K., Seredyński, D.: Multi-sensory feedback control in door approaching and opening. In: Filev, D., Jabłkowski, J., Kacprzyk, J., Krawczak, M., Popchev, I., Rutkowski, L., Sgurev, V., Sotirova, E., Szynkarczyk, P., Zadrozny, S. (eds.) Intelligent Systems’2014. Advances in Intelligent Systems and Computing, vol. 323, pp. 57–70. Springer International Publishing (2015)Google Scholar
  3. 3.
    Jean-Pierre, G., Said, Z.: The artist robot: a robot drawing like a human artist. In: 2012 IEEE International Conference on Industrial Technology (ICIT), pp. 486–491 (March 2012)Google Scholar
  4. 4.
    Zieliński, C., Winiarski, T.: General specification of multi-robot control system structures. Bull. Pol. Acad. Sci.—Tech. Sci. 58(1), 15–28 (2010)Google Scholar
  5. 5.
    Lin, C.Y., Chuang, L.W., Mac, T.T.: Human portrait generation system for robot arm drawing. In: IEEE/ASME International Conference on Advanced Intelligent Mechatronics. AIM 2009, pp. 1757–1762 (July 2009)Google Scholar
  6. 6.
    Tresset, P., Leymarie, F.F.: Portrait drawing by paul the robot. Comput. Graph. 37(5), 348–363 (2013)CrossRefGoogle Scholar
  7. 7.
    Junyou, Y., Guilin, Q., Le, M., Dianchun, B., Xu, H.: Behavior-based control of brush drawing robot. In: 2011 International Conference on Transportation, Mechanical, and Electrical Engineering (TMEE), pp. 1148–1151 (Dec 2011)Google Scholar
  8. 8.
    Jain, S., Gupta, P., Kumar, V., Sharma, K.: A force-controlled portrait drawing robot. In: 2015 IEEE International Conference on Industrial Technology (ICIT), pp. 3160–3165 (March 2015)Google Scholar
  9. 9.
    Chenavier, F., Crowley, J.: Position estimation for a mobile robot using vision and odometry. In: 1992 IEEE International Conference on Robotics and Automation. Proceedings., vol. 3, pp. 2588–2593 (May 1992)Google Scholar
  10. 10.
    Yagi, Y., Kawato, S., Tsuji, S.: Real-time omnidirectional image sensor (copis) for vision-guided navigation. IEEE Trans. Robot. Autom. 10(1), 11–22 (1994)CrossRefGoogle Scholar
  11. 11.
    Brosnan, T., Sun, D.W.: Improving quality inspection of food products by computer vision—a review. J. Food Eng. 61(1), 3–16 (2004)CrossRefGoogle Scholar
  12. 12.
    Sharp, C., Shakernia, O., Sastry, S.: A vision system for landing an unmanned aerial vehicle. In: IEEE International Conference on Robotics and Automation. Proceedings 2001 ICRA, vol. 2, pp. 1720–1727 (2001)Google Scholar
  13. 13.
    Zieliński, C., Kornuta, T., Winiarski, T.: A systematic method of designing control systems for service and field robots. In: 19-th IEEE International Conference on Methods and Models in Automation and Robotics, MMAR’2014, pp. 1–14. IEEEGoogle Scholar
  14. 14.
    Kasprzak, W., Kornuta, T., Zieliński, C.: A virtual receptor in a robot control framework. In: Recent Advances in Automation, Robotics and Measuring Techniques. Advances in Intelligent Systems and Computing (AISC). Springer (2014)Google Scholar
  15. 15.
    Staniak, M., Winiarski, T., Zieliński, C.: Parallel visual-force control. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS ’08 (2008)Google Scholar
  16. 16.
    Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. (6), 679–698 (1986)Google Scholar
  17. 17.
    Kiryati, N., Eldar, Y., Bruckstein, A.M.: A probabilistic hough transform. Pattern Recognit. 24(4), 303–316 (1991)CrossRefMathSciNetGoogle Scholar
  18. 18.
    Mikolajczyk, K., Schmid, C.: An affine invariant interest point detector. In: Computer Vision—ECCV 2002, pp. 128–142. Springer (2002)Google Scholar
  19. 19.
    Udrea, R.M., Vizireanu, N.: Iterative generalization of morphological skeleton. J. Electron. Imaging 16(1), 010501–010501 (2007)CrossRefGoogle Scholar
  20. 20.
    Suzuki, S., et al.: Topological structural analysis of digitized binary images by border following. Comput. Vis., Graph., Image Process. 30(1), 32–46 (1985)CrossRefzbMATHGoogle Scholar
  21. 21.
    Quan, L., Lan, Z.: Linear n-point camera pose determination. IEEE Trans. Pattern Anal. Mach. Intell. 21(8), 774–780 (1999)CrossRefGoogle Scholar
  22. 22.
    Walcki, M., Banachowicz, K., Winiarski, T.: Research oriented motor controllers for robotic applications. In: Kozłowski, K. (ed.) Robot Motion and Control 2011 (LNCiS) Lecture Notes in Control & Information Sciences, vol. 422, pp. 193–203. Springer Verlag London Limited (2012)Google Scholar
  23. 23.
    Winiarski, T., Banachowicz, K.: Automated generation of component system for the calibration of the service robot kinematic parameters. In: 20th IEEE International Conference on Methods and Models in Automation and Robotics, MMAR’2015. IEEE (2015)Google Scholar
  24. 24.
    Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.Y.: ROS: an open-source robot operating system. In: ICRA Workshop on Open Source Software, vol. 3 (2009)Google Scholar
  25. 25.
    Bruyninckx, H., Soetens, P., Koninckx, B.: The real-time motion control core of the orocos project. In: IEEE International Conference on Robotics and Automation. Proceedings. ICRA ’03, vol. 2, pp. 2766–2771 (Sept 2003)Google Scholar
  26. 26.
    Stefańczyk, M., Kornuta, T.: Handling of asynchronous data flow in robot perception subsystems. In: Simulation, Modeling, and Programming for Autonomous Robots. Lecture Notes in Computer Science, vol. 8810, pp. 509–520. Springer (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Warsaw University of TechnologyWarsawPoland

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