Virtual Reality

, Volume 11, Issue 4, pp 241–252

Factors affecting user performance in haptic assembly

  • T. Lim
  • J. M. Ritchie
  • R. G. Dewar
  • J. R. Corney
  • P. Wilkinson
  • M. Calis
  • M. Desmulliez
  • J.-J. Fang
Original Article
  • 274 Downloads

Abstract

Current computer-aided assembly systems provide engineers with a variety of spatial snapping and alignment techniques for interactively defining the positions and attachments of components. With the advent of haptics and its integration into virtual assembly systems, users now have the potential advantage of tactile information. This paper reports research that aims to quantify how the provision of haptic feedback in an assembly system can affect user performance. To investigate human–computer interaction processes in assembly modeling, performance of a peg-in-hole manipulation was studied to determine the extent to which haptics and stereovision may impact on task completion time. The results support two important conclusions: first, it is apparent that small (i.e. visually insignificant) assembly features (e.g. chamfers) affect the overall task completion at times only when haptic feedback is provided; and second, that the difference is approximately similar to the values reported for equivalent real world peg-in-hole assembly tasks.

Keywords

Haptic assembly Human–computer Interaction Human factors Design for assembly Peg-in-hole metrics Virtual reality 

References

  1. Amirabdollahian F, Gomes GT, Johnson GR (2005) The peg-in-hole: a VR-based haptic assessment for quantifying upper limb performance and skills. In: Proceedings of the 9th IEEE international conference on rehabilitation robotics, pp 422–425Google Scholar
  2. Bashir AB, Bicker R, Taylor PM (2004) An investigation into different visual/tactual feedback modes for a virtual object manipulation task. In: Proceedings of the ACM SIGGRAPH international conference on virtual reality continuum and its applications in industry, pp 359–362Google Scholar
  3. Boothroyd G, Dewhurst P, Knight W (2002) Product design for manufacture and assembly, 2nd edn. ISBN 0-8247-0584-XGoogle Scholar
  4. Brooke J (1996) SUS—a quick and dirty usability scale. Redhatch Consulting Ltd., 12 Beaconsfield Way, Earley, Reading RG62UX, UKGoogle Scholar
  5. Caselli S, Magnanini C, Zanichelli F, Caraffi E (1996) Efficient exploration and recognition of convex objects based on haptic perception. Proc IEEE Int Conf Robot Autom 4:3508–3513Google Scholar
  6. Fitts PM (1954) The information capacity of human motor systems in controlling the amplitude of a movement. J Exp Psychol 47:381–391CrossRefGoogle Scholar
  7. Gerovichev O, Marayong P, Okamura AM (2002) The effect of visual and haptic feedback on manual and teleoperated needle insertion. In: Proceedings of the 5th international conference on medical image computing and computer-assisted intervention, Part I, vol 2488, pp 147–154Google Scholar
  8. Gosset, William Sealy 1876-1937 (1970). In: Pearson ES, Kendall MG (eds) Studies in the history of statistics and probability, pp 355–404Google Scholar
  9. Gupta R, Whitney D, Zeltzer D (1997) Prototyping and design for assembly analysis using multimodal virtual environments. CAD 29(8):585–597Google Scholar
  10. Haeusler J (1981) Design for assembly—state-of-the-art. In: Proceedings of the 2nd international conference on assembly automation, Brighton, pp 109–128. ISBN 0903608162Google Scholar
  11. Hara K, Yokogawa R, Kai Y (1997) Evaluation of task-performance of a manipulator for a peg-in-hole task. In: Proceedings of IEEE international conference on robotics and automation, Albuquerque, New Mexico, pp 600–605Google Scholar
  12. Ho C, Boothroyd G (1979) Design of chamfers for ease of assembly. In: Proceedings of the 7th manuf eng trans North AME metalwork res conf, pp 345–354Google Scholar
  13. Johan T, Jan W (2005) Tactile sensing in intelligent robotic manipulation—a review. Ind Robot 32/1:64–70Google Scholar
  14. Kim IW, Lim DJ, Kim KI (1999) Active peg-in-hole of chamferless parts using force/moment sensor. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems, pp 948–953Google Scholar
  15. Lim T, Dewar R, Calis M, Ritchie JM, Corney JR, Desmulliez M (2006) A structural assessment of haptic-based assembly processes. In: 1st international virtual manufacturing workshop (VirMan’06), 26 March 2006, Virginia, USA, vol 29Google Scholar
  16. Massie T, Salisbury K (1994) The PHANTom haptic interface: a device for probing virtual objects. ASME Winter Annual Meeting, DSC, vol 55-1, pp 295–300Google Scholar
  17. Massimo MJ, Sheridan TB (1993) Sensory substitution for force feedback in teleoperation. Presence Teleoper Virtual Environ 2(4):344–352Google Scholar
  18. Okamura AM, Turner ML, Cutkosky MR (1997) Haptic exploration of objects with rolling and sliding. IEEE international conference on robotics and automation, Albuquerque, New Mexico, pp 2485–2490Google Scholar
  19. Rosenberg, LB (1993) Virtual fixtures: perceptual tools for telerobotic manipulation. In: IEEE virtual reality annual international symposium, pp 76–82Google Scholar
  20. Rosenberg L (1994) Virtual fixtures. PhD Dissertation, Stanford UniversityGoogle Scholar
  21. Sener B, Wormald P, Campbell I (2002) Evaluating a haptic modelling system with industrial designers. In: Proceedings of the EuroHaptics international conference, Edinburgh, Scotland, pp 165–170Google Scholar
  22. Sheridan TB (1992) Telerobotics, automation and human supervisory control. MIT Press, CambridgeGoogle Scholar
  23. Unger BJ, Nicoladis A, Berkelman PJ, Thompson A, Klatzky RL, Hollis RL (2001) Comparison of 3-D haptic peg-in-hole tasks in real and virtual environments. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems, pp 1751–1756Google Scholar
  24. Yoshikawa T, Kawai M, Yoshimoto K (2003) Toward observation of human assembly skill using virtual task space. Experimental Robotics VIII, STAR 5, pp 540–549Google Scholar

Copyright information

© Springer-Verlag London Limited 2007

Authors and Affiliations

  • T. Lim
    • 1
  • J. M. Ritchie
    • 1
  • R. G. Dewar
    • 1
  • J. R. Corney
    • 1
  • P. Wilkinson
    • 1
  • M. Calis
    • 1
  • M. Desmulliez
    • 1
  • J.-J. Fang
    • 2
  1. 1.Scottish Manufacturing InstituteHeriot-Watt UniversityEdinburghScotland, UK
  2. 2.Department of Mechanical EngineeringNational Cheng Kung UniversityTainanTaiwan

Personalised recommendations