The Visual Computer

, Volume 33, Issue 1, pp 63–74 | Cite as

Customization and fabrication of the appearance for humanoid robot

  • Shihui GuoEmail author
  • Hanxiang Xu
  • Nadia Magnenat Thalmann
  • Junfeng Yao
Original Article


Designing a robot’s appearance is a challenging task because the design should be both aesthetically appealing and physically functional. Therefore, this task was previously limited to experts with professional knowledge and experiences. Given the increasing popularity of consumer-level robots, non-professional users are expecting tools that allow them to customize their robot appearance. We address this challenge with the technology of additive manufacturing and propose an end-to-end solution to customize and fabricate the robot appearance for non-professional users. The input to our solution is a triangular character mesh (commonly used in feature animations and video games) and the output is a set of 3D-printing-ready shell parts. The complete solution includes matching the shape of the character mesh with the robot endoskeleton, optimizing the shape design to maximally avoid collisions and adjusting the motion trajectories to adapt to new shell design. This approach requires no professional background in engineering design and efficiently produces accurate prototypes of robot shells. Both virtual and physically printed designs are demonstrated on a consumer level humanoid robot to validate the feasibility of our method.


Additive Manufacturing Humanoid Robot Sequential Quadratic Programming Collision Detection Acrylonitrile Butadiene Styrene 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This research, which is carried out at BeingThere Centre, collaboration among IMI of Nanyang Technological University (NTU) Singapore, ETH Zürich, and UNC Chapel Hill, is supported by the Singapore National Research Foundation (NRF) under its International Research Centre @ Singapore Funding Initiative and administered by the Interactive Digital Media Programme Office (IDMPO).

Supplementary material

Supplementary material 1 (mp4 11960 KB)


  1. 1.
    Aldebaran: Cool robots. (2016). Accessed: 2016-05-06
  2. 2.
    Bächer, M., Bickel, B., James, D.L., Pfister, H.: Fabricating articulated characters from skinned meshes. ACM Trans. Graph. (TOG) 31(4), 47 (2012)CrossRefGoogle Scholar
  3. 3.
    Bächer, M., Whiting, E., Bickel, B., Sorkine-Hornung, O.: Spin-it: optimizing moment of inertia for spinnable objects. ACM Trans. Graph. (TOG) 33(4), 96 (2014)CrossRefGoogle Scholar
  4. 4.
    Byrd, R.H., Nocedal, J., Waltz, R.A.: Knitro: An integrated package for nonlinear optimization. In: Large-scale nonlinear optimization, Springer, pp. 35–59 (2006)Google Scholar
  5. 5.
    Calì, J., Calian, D.A., Amati, C., Kleinberger, R., Steed, A., Kautz, J., Weyrich, T.: 3d-printing of non-assembly, articulated models. ACM Trans. Graph. (TOG) 31(6), 130 (2012)CrossRefGoogle Scholar
  6. 6.
    Coros, S., Thomaszewski, B., Noris, G., Sueda, S., Forberg, M., Sumner, R.W., Matusik, W., Bickel, B.: Computational design of mechanical characters. ACM Trans. Graph. (TOG) 32(4), 83 (2013)CrossRefzbMATHGoogle Scholar
  7. 7.
    Coumans, E.: Bullet physics engine. Open Source Software: 1 (2010)
  8. 8.
    Flowers, L.: Poppy project. (2016). Accessed: 2016-03-21
  9. 9.
    Fu, C.W., Chi-Wing, F., Peng, S., Xiaoqi, Y., Yang, L.W., Jayaraman, P.K., Daniel, C.O.: Computational interlocking furniture assembly. ACM Trans. Graph. (TOG) 34(4), 91:1–91:11 (2015)CrossRefzbMATHGoogle Scholar
  10. 10.
    Golovinskiy, A., Aleksey, G., Thomas, F.: Consistent segmentation of 3D models. Comput. Graph. 33(3), 262–269 (2009)CrossRefGoogle Scholar
  11. 11.
    Hao, J., Jingbin, H., Liang, F., Williams, R.E.: An efficient curvature-based partitioning of large-scale STL models. Rapid Prototyp. J. 17(2), 116–127 (2011)CrossRefGoogle Scholar
  12. 12.
    Haring, K.S., Katsumi, W., Celine, M.: The influence of robot appearance on assessment. In: 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (2013)Google Scholar
  13. 13.
    Hildebrand, K., Kristian, H., Bernd, B., Marc, A.: Orthogonal slicing for additive manufacturing. Comput. Graph. 37(6), 669–675 (2013)CrossRefGoogle Scholar
  14. 14.
    Hu, R., Ruizhen, H., Honghua, L., Hao, Z., Daniel, C.O.: Approximate pyramidal shape decomposition. ACM Trans. Graph. (TOG) 33(6), 1–12 (2014)Google Scholar
  15. 15.
    van Kaick, O., Andrea, T., Oana, S., Hao, Z., Daniel, C.O., Lior, W., Ghassan, H.: Prior knowledge for part correspondence. Comput. Graph. Forum 30(2), 553–562 (2011)CrossRefGoogle Scholar
  16. 16.
    Kajita, S., Kanehiro, F., Kaneko, K., Fujiwara, K., Harada, K., Yokoi, K., Hirukawa, H.: Biped walking pattern generation by using preview control of zero-moment point. In: Robotics and Automation, 2003. Proceedings. ICRA’03. IEEE International Conference on, vol. 2, pp. 1620–1626. IEEE (2003)Google Scholar
  17. 17.
    Koo, B., Li, W., Yao, J., Agrawala, M., Mitra, N.J.: Creating works-like prototypes of mechanical objects. ACM Transactions on Graphics (Special issue of SIGGRAPH Asia 2014) (2014)Google Scholar
  18. 18.
    Langevin, G.: Inmoov project. (2016). Accessed: 2016-03-21
  19. 19.
    LEGO: Mindstorms. (2016). Accessed: 2016-05-06
  20. 20.
    Megaro, V., Thomaszewski, B., Gauge, D., Grinspun, E., Coros, S., Gross, M.H.: Chacra: An interactive design system for rapid character crafting. In: Symposium on Computer Animation, pp. 123–130 (2014)Google Scholar
  21. 21.
    Megaro, V., Vittorio, M., Bernhard, T., Maurizio, N., Otmar, H., Markus, G., Stelian, C.: Interactive design of 3d-printable robotic creatures. ACM Trans. Graph. (TOG) 34(6), 1–9 (2015)CrossRefGoogle Scholar
  22. 22.
    Mehta, A.M., DelPreto, J., Shaya, B., Rus, D.: Cogeneration of mechanical, electrical, and software designs for printable robots from structural specifications. In: Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on, pp. 2892–2897. IEEE (2014)Google Scholar
  23. 23.
    Mehta, A.M., Rus, D.: An end-to-end system for designing mechanical structures for print-and-fold robots. In: Robotics and Automation (ICRA), 2014 IEEE International Conference on, pp. 1460–1465. IEEE (2014)Google Scholar
  24. 24.
    Prévost, R., Whiting, E., Lefebvre, S., Sorkine-Hornung, O.: Make it stand: balancing shapes for 3d fabrication. ACM Trans. Graph. (TOG) 32(4), 81 (2013)CrossRefzbMATHGoogle Scholar
  25. 25.
    Robotics, T.: Hr-os1 humanoid endoskeleton. (2016). Accessed: 2016-03-21
  26. 26.
    Robotis: Ax-12a actuator e-manual. (2016). Accessed: 2016-05-11
  27. 27.
    Robotis: Open platform humanoid project. (2016). Accessed: 2016-03-21
  28. 28.
    Shapira, L., Shalom, S., Shamir, A., Cohen-Or, D., Zhang, H.: Contextual part analogies in 3d objects. Int. J. Comput. Vision 89(2), 309–326 (2010)CrossRefGoogle Scholar
  29. 29.
    Shapira, L., Shamir, A., Cohen-Or, D.: Consistent mesh partitioning and skeletonisation using the shape diameter function. Visual Comput. 24(4), 249–259 (2008)CrossRefGoogle Scholar
  30. 30.
    Skouras, M., Mélina, S., Bernhard, T., Stelian, C., Bernd, B., Markus, G.: Computational design of actuated deformable characters. ACM Trans. Graph. (TOG) 32(4), 1 (2013)CrossRefGoogle Scholar
  31. 31.
    Slyper, R., Ronit, S., Jessica, H.: Prototyping robot appearance, movement, and interactions using flexible 3D printing and air pressure sensors. In: 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication (2012)Google Scholar
  32. 32.
    Song, P., Peng, S., Zhongqi, F., Ligang, L., Chi-Wing, F.: Printing 3D objects with interlocking parts. Comput. Aided Geom. Des. 35–36, 137–148 (2015)MathSciNetCrossRefGoogle Scholar
  33. 33.
    Syrdal, D.S., Dautenhahn, K., Woods, S.N., Walters, M.L., Koay, K.L.: Looking good? appearance preferences and robot personality inferences at zero acquaintance. In AAAI Spring Symposium: Multidisciplinary Collaboration for Socially Assistive Robotics pp. 86–92 (2007)Google Scholar
  34. 34.
    The CGAL Project: CGAL User and Reference Manual, 4.8 edn. CGAL Editorial Board (2016).
  35. 35.
    Thomaszewski, B., Bernhard, T., Stelian, C., Damien, G., Vittorio, M., Eitan, G., Markus, G.: Computational design of linkage-based characters. ACM Trans. Graph. (TOG) 33(4), 1–9 (2014)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Institute for Media InnovationNanyang Technological UniversitySingaporeSingapore
  2. 2.School of SoftwareXiamen UniversityXiamenChina

Personalised recommendations