An All-in-One Robotic Platform for Hybrid Manufacturing of Large Volume Parts

  • Francesco CrivelliEmail author
  • Valentin Baumann
  • Markus Steiner
  • Mark D’Urso
  • Philipp Schmid
  • Alexander Steinecker
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 530)


3D printing offers many advantages over conventional machining and its applications in industrial manufacturing is growing. However, existing additive technologies present limitations in workspace volume, accuracy and surface quality. These limitations could be overcome by combining both additive and subtractive processes. Such hybrid approaches allow layer-by-layer construction, alternating fast and rough material deposition with machining steps, when the layer’s geometry is finished. Despite its potential, the development and industrial application of hybrid machines is slow. Particularly, no systems exist for the construction of large parts. The project KRAKEN is well-situated in this context, aiming at the development of a novel, fully automated, all-in-one platform for large volume hybrid manufacturing. This powerful tool will not only combine additive with subtractive processes, but it will also include both metal and non-metal 3D printing, resulting in a completely new machine for the construction of large, multi-material parts. A control approach based on direct measurement of the end-effector position will allow a combination of large workspace (up to 20 m) and high manufacturing accuracy (tolerances < 0.3 mm, surface roughness Ra < 0.1 µm). This paper presents the preliminary steps toward the development of this robotic platform, focusing on the use of the real-time feedback of an absolute laser tracker to control motion and positioning of the manufacturing robot. The proposed control strategy is presented and discussed. Finally, the use of an Extended Kalman Filter to fuse the laser measurement with the robot position sensors is presented and discussed based on offline evaluation.


Hybrid manufacturing Large parts Multi-material All-in-one machine Robotic manufacturing Extended Kalman Filter 



This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 723759. Their support is gratefully acknowledged.


  1. 1.
    Berman, B.: 3-D printing: The new industrial revolution. Bus. Horiz. 55(2), 155–162 (2012)CrossRefGoogle Scholar
  2. 2.
    Wohlers, T.T.: 3D printing and additive manufacturing state of the industry annual worldwide progress report. Wohlers report, Wohlers Associates (2014)Google Scholar
  3. 3.
    Allison, A., Scudamore, R.: Additive Manufacturing: Strategic Research Agenda. TWI, Cambridge (2014)Google Scholar
  4. 4.
    Flynn, J.M., Shokrani, A., Newman, S.T., Dhokia, V.: Hybrid additive and subtractive machine tools - research and industrial developments. Int. J. Mach. Tools Manuf 101, 79–102 (2016)CrossRefGoogle Scholar
  5. 5.
    Akula, S., Karunakaran, K.P.: Hybrid adaptive layer manufacturing: an Intelligent art of direct metal rapid tooling process. Robot. Comput.-Integr. Manuf. 22(2), 113–123 (2006)CrossRefGoogle Scholar
  6. 6.
    Karunakaran, K.P., Suryakumar, S., Pushpa, V., Akula, S.: Low cost integration of additive and subtractive processes for hybrid layered manufacturing. Robot. Comput.-Integr. Manuf. 26(5), 490–499 (2010)CrossRefGoogle Scholar
  7. 7.
    Kraken project homepage. Accessed 31 Oct 2017
  8. 8.
    Megarob project homepage. Accessed 31 Oct 2017
  9. 9.
    Shirinzadeh, B., Teoh, P.L., Tian, Y., Dalvand, M.M., Zhong, Y., Liaw, H.C.: Laser interferometry-based guidance methodology for high precision positioning of mechanisms and robots. Robot. Comput.-Integr. Manuf. 26(1), 74–82 (2010)CrossRefGoogle Scholar
  10. 10.
    Möller, C., Schmidt, H.C.: Real-Time 7DoF Pose Control of an Industrial Robotic System for Machining of Large-Scale CFRP Parts in the Aerospace Industry. Fraunhofer IFAM, Stade (2017)Google Scholar
  11. 11.
    Droll, S.: Real time path correction of a KUKA robot with optical feedback from a Leica laser tracker. Master Thesis, ETH Zurich, Zurich (2013)Google Scholar
  12. 12.
    Sciavicco, L., Siciliano, B.: Modelling and Control of Robot Manipulators. Springer, London (2012)zbMATHGoogle Scholar
  13. 13.
    Veldpaus, F.E., Woltring, H.J., Dortmans, L.J.M.G.: A least-squares algorithm for the equiform transformation from spatial marker co-ordinates. J. Biomech. 21(1), 45–54 (1988)CrossRefGoogle Scholar
  14. 14.
    Jazwinski, A.H.: Stochastic Processes and Filtering. Dover Publications, New York (1970)zbMATHGoogle Scholar
  15. 15.
    Julier, S.J., Uhlmann, J.K.: Unscented filtering and nonlinear estimation. Proc. IEEE 92(3), 401–422 (2004)CrossRefGoogle Scholar
  16. 16.
    Boesel, D.F., Glocker, P., Dienste, J.A., Peinado, V.: Realtime control of absolute Cartesian position of industrial robot for machining of large parts. In: Austrian Robotics Workshop 2015, p. 9. Klaugenfurt (2015)Google Scholar
  17. 17.
    Lightcap, C.A., Banks, S.A.: An extended Kalman filter for real-time estimation and control of a rigid-link flexible-joint manipulator. IEEE Trans. Control Syst. Technol. 18(1), 91–103 (2010)CrossRefGoogle Scholar
  18. 18.
    Jassemi-Zargani, R., Necsulescu, D.: Extended Kalman filter-based sensor fusion for operational space control of a robot arm. IEEE Trans. Instrum. Meas. 51(6), 1279–1282 (2002)CrossRefGoogle Scholar
  19. 19.
    Chen, S.Y.: Kalman filter for robot vision: a survey. IEEE Trans. Industr. Electron. 59(11), 4409–4420 (2012)CrossRefGoogle Scholar
  20. 20.
    Trawny, N., Roumeliotis, S.I.: Indirect Kalman filter for 3D attitude estimation. Department of Computer Science and Engineering, University of Minnesota, Minnesota (2005)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  • Francesco Crivelli
    • 1
    Email author
  • Valentin Baumann
    • 2
  • Markus Steiner
    • 2
  • Mark D’Urso
    • 2
  • Philipp Schmid
    • 1
  • Alexander Steinecker
    • 1
  1. 1.CSEM SAAlpnach DorfSwitzerland
  2. 2.Hexagon Manufacturing IntelligenceUnterentfeldenSwitzerland

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