ICoRD'13 pp 423-434 | Cite as

Preliminary Analysis of Low-Cost Motion Capture Techniques to Support Virtual Ergonomics

  • Giorgio Colombo
  • Daniele Regazzoni
  • Caterina Rizzi
  • Giordano De Vecchi
Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

This paper concerns the development of a computer-aided platform to analyze workers’ postures and movements and ergonomically validate the design of device a man or woman may deal with. In particular, we refer to pick and place operations of food items on the display unit shelves. The paper describes three low-cost solutions that integrate two optical motion capture techniques (one based on web-cam and another on MS Kinect sensor) and two human modeling systems (Jack and LifeMod) with the main goal of determining the suitability of operators’ working conditions and, eventually, providing a feedback to the design step. The solutions have been tested considering a vertical display unit as case study. Preliminary results of the experimentation as well as main benefits and limits are presented. The results have been considered promising; however, we have planned to perform an acquisition campaign in the real environment, the supermarket.

Keywords

Human modeling Motion capture Virtual ergonomics Pick and place 

References

  1. 1.
    Colombo G, De Ponti G, Rizzi C (2010) Ergonomic design of refrigerated display units. Virtual Phys Prototyping 3(5):139–152CrossRefGoogle Scholar
  2. 2.
    Sundin A, Ortengren R (2006) Digital human modelling for CAE applications, handbook of human factors and ergonomics, 3rd edn. Wiley, New YorkGoogle Scholar
  3. 3.
    Magnenat-Thalmann N, Thalmann D (2004) Handbook of virtual humans. Wiley, ChichesterCrossRefGoogle Scholar
  4. 4.
    Rizzi C (2011) Digital human models within product development process innovation in product design. Springer, Berlin, pp 143–166Google Scholar
  5. 5.
    http://www.massivesoftware.com. Accessed July 2012
  6. 6.
  7. 7.
    Wang CCL, Wang Y, Chang TKK, Yuen MMF (2003) Virtual human modeling from photographs for garment industry. Comput-Aided Des 35(6):577–589Google Scholar
  8. 8.
    Li SSM, Wang CCL, Hui Kin-Chuen (2011) Bending-invariant correspondence matching on 3D human bodies for feature point extraction. IEEE Trans Autom Sci Eng 8(4):805–814CrossRefGoogle Scholar
  9. 9.
    Colombo G, Cugini U (2005) Virtual humans and prototypes to evaluate ergonomics and safety. J Eng Design 16(2):195–203CrossRefGoogle Scholar
  10. 10.
    Mueller A, Maier T (2009) Vehicle layout conception considering vision requirements—a comparative study within manual assembly of automobiles. Digital human modeling for design and engineering conference and exhibitionGoogle Scholar
  11. 11.
    Green RF, Hudson JA (2011) A method for positioning digital human models in airplane passenger seats, advances in applied digital human modeling. CRC Press, Boca RatonGoogle Scholar
  12. 12.
    Abdel-Malek K et al (2009) A physics-based digital human model. Int J Veh Des 51(3/4):324–340CrossRefGoogle Scholar
  13. 13.
    http://www.lifemodeler.com. Accessed July 2012
  14. 14.
    Bucca G, Buzzolato A, Bruni S (2009) A mechatronic device for the rehabilitation of ankle motor function. J Biomech Eng 131(12):125001Google Scholar
  15. 15.
    Furniss M (2012) Motion capture. MIT communications forum http://web.mit.edu/ commforum/papers/furniss.html. Accessed July 2012
  16. 16.
    Schepers HM (2009) Ambulatory assessment of human body kinematics and kinetics. Ph. d thesis, UniversiteitTwente, The Netherlands. Available at http://www.xsens.com/images/stories/PDF/ThesisSchepers.pdf
  17. 17.
    http://www.vicon.com. Accessed July 2012
  18. 18.
    Bray J (2012) Markerless based human motion Capture: a survey. Vision and VR Group, Department of Systems Engineering, Brunel University, available at http://visicast.co.uk/members/move/Partners/Papers/MarkerlessSurvey.pdf. Accessed July 2012
  19. 19.
    Colombo G, De Angelis F, Formentini L (2010) Integration of virtual reality and haptics to carry out ergonomic tests on virtual control boards. Int J Prod Dev 11(1/2):47–61CrossRefGoogle Scholar
  20. 20.
    Spada S, Sessa F, Corato F (2012) Virtual reality tools for statistical analysis for human movement simulation. Application to ergonomics optimization of work cells in the automotive industry. Work 41:6120–6126Google Scholar
  21. 21.
    Cheng H (1996) The development of the GEBOD program. In: Proceedings of the 1996 fifteenth southern biomedical engineering conference, pp 251–254Google Scholar
  22. 22.
    People size database of anthropometric measure Available at http://www.openerg.com/psz/anthropometric_dates.html. Accessed October 2012
  23. 23.
    NSRDEC: US Army Natick Soldier Research Development and Engineering Center, http://nsrdec.natick.army.mil/ANSURII/index.htm. Accessed October 2012

Copyright information

© Springer India 2013

Authors and Affiliations

  • Giorgio Colombo
    • 1
  • Daniele Regazzoni
    • 2
  • Caterina Rizzi
    • 2
  • Giordano De Vecchi
    • 2
  1. 1.Department of MechanicsPolytechnic of MilanMilanItaly
  2. 2.Department of EngineeringUniversity of BergamoDalmineItaly

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