“An interaction-aware, perceptual model for non-linear elastic objects” by Piovarči and Levin

  • ©

Conference:


Type(s):


Title:

    An interaction-aware, perceptual model for non-linear elastic objects

Session/Category Title:   PERCEPTION OF SHAPES AND PEOPLE

Presenter(s)/Author(s):


Moderator(s):


Abstract:


    Everyone, from a shopper buying shoes to a doctor palpating a growth, uses their sense of touch to learn about the world. 3D printing is a powerful technology because it gives us the ability to control the haptic impression an object creates. This is critical for both replicating existing, real-world constructs and designing novel ones. However, each 3D printer has different capabilities and supports different materials, leaving us to ask: How can we best replicate a given haptic result on a particular output device? In this work, we address the problem of mapping a real-world material to its nearest 3D printable counterpart by constructing a perceptual model for the compliance of nonlinearly elastic objects. We begin by building a perceptual space from experimentally obtained user comparisons of twelve 3D-printed metamaterials. By comparing this space to a number of hypothetical computational models, we identify those that can be used to accurately and efficiently evaluate human-perceived differences in nonlinear stiffness. Furthermore, we demonstrate how such models can be applied to complex geometries in an interaction-aware way where the compliance is influenced not only by the material properties from which the object is made but also its geometry. We demonstrate several applications of our method in the context of fabrication and evaluate them in a series of user experiments.

References:


    1. Ambrosi, G., Bicchi, A., Rossi, D. D., and Scilingo, E. P. 1999. The role of contact area spread rate in haptic discrimination of softness. In Robotics and Automation, 1999. Proceedings. 1999 IEEE International Conference on, vol. 1, 305–310 vol. 1.Google Scholar
    2. Bergmann Tiest, W. M., and Kappers, A. M. 2006. Analysis of haptic perception of materials by multidimensional scaling and physical measurements of roughness and compressibility. Acta psychologica 121, 1, 1–20.Google Scholar
    3. Bickel, B., Bächer, M., Otaduy, M. A., Lee, H. R., Pfister, H., Gross, M., and Matusik, W. 2010. Design and fabrication of materials with desired deformation behavior. ACM Transactions on Graphics (TOG) 29, 4, 63. Google ScholarDigital Library
    4. Bonneel, N., van de Panne, M., Paris, S., and Heidrich, W. 2011. Displacement interpolation using lagrangian mass transport. ACM Trans. Graph. 30, 6, 158:1–158:12. Google ScholarDigital Library
    5. Chen, D., Levin, D. I., Didyk, P., Sitthi-Amorn, P., and Matusik, W. 2013. Spec2fab: a reducer-tuner model for translating specifications to 3D prints. ACM Transactions on Graphics (TOG) 32, 4, 135. Google ScholarDigital Library
    6. Cook, R. L. 1986. Stochastic sampling in computer graphics. ACM Trans. Graph. 5, 1 (Jan.), 51–72. Google ScholarDigital Library
    7. Cooke, T., Kannengiesser, S., Wallraven, C., and Bülthoff, H. H. 2006. Object feature validation using visual and haptic similarity ratings. ACM Transactions on Applied Perception (TAP) 3, 3, 239–261. Google ScholarDigital Library
    8. Cooke, T., Wallraven, C., and Bülthoff, H. H. 2010. Multidimensional scaling analysis of haptic exploratory procedures. ACM Transactions on Applied Perception (TAP) 7, 1, 7. Google ScholarDigital Library
    9. Davison, A. C., and Hinkley, D. V. 1997. Bootstrap Methods and their Application. Cambridge University Press.Google Scholar
    10. Friedman, R. M., Hester, K. D., Green, B. G., and LaMotte, R. H. 2008. Magnitude estimation of softness. Experimental brain research 191, 2, 133–142.Google Scholar
    11. Genecov, A. M., Stanley, A. A., and Okamura, A. M. 2014. Perception of a haptic jamming display: Just noticeable differences in stiffness and geometry. In Haptics Symposium (HAPTICS), 2014 IEEE, IEEE, 333–338.Google Scholar
    12. Gkioulekas, I., Xiao, B., Zhao, S., Adelson, E. H., Zickler, T., and Bala, K. 2013. Understanding the role of phase function in translucent appearance. ACM Transactions on Graphics (TOG) 32, 5, 147. Google ScholarDigital Library
    13. Han, D., and Keyser, J. 2015. Effect of appearance on perception of deformation. In Proceedings of the 14th ACM SIGGRAPH / Eurographics Symposium on Computer Animation, ACM, New York, NY, USA, SCA ’15, 37–44. Google ScholarDigital Library
    14. Harper, R., and Stevens, S. 1964. Subjective hardness of compliant materials. Quarterly Journal of Experimental Psychology 16, 3, 204–215.Google ScholarCross Ref
    15. Hastie, T., Tibshirani, R., Friedman, J., Hastie, T., Friedman, J., and Tibshirani, R. 2009. The elements of statistical learning, vol. 2. Springer.Google Scholar
    16. Hollins, M., Bensmaïa, S., Karlof, K., and Young, F. 2000. Individual differences in perceptual space for tactile textures: Evidence from multidimensional scaling. Perception & Psychophysics 62, 8, 1534–1544.Google ScholarCross Ref
    17. Jones, L. A., and Hunter, I. W. 1990. A perceptual analysis of stiffness. Experimental Brain Research 79, 1, 150–156.Google ScholarCross Ref
    18. Koçak, U., Palmerius, K. L., Forsell, C., Ynnerman, A., and Cooper, M. 2011. Analysis of the JND of stiffness in three modes of comparison. In Haptic and Audio Interaction Design. Springer, 22–31. Google ScholarDigital Library
    19. Kuschel, M., Di Luca, M., Buss, M., and Klatzky, R. L. 2010. Combination and integration in the perception of visual-haptic compliance information. Haptics, IEEE Transactions on 3, 4, 234–244. Google ScholarDigital Library
    20. Lederman, S. J., and Klatzky, R. L. 2009. Haptic perception: A tutorial. Attention, Perception, & Psychophysics 71, 7, 1439–1459.Google ScholarCross Ref
    21. Leib, R., Nisky, I., and Karniel, A. 2010. Perception of stiffness during interaction with delay-like nonlinear force field. In Haptics: Generating and Perceiving Tangible Sensations. Springer, 87–92. Google ScholarDigital Library
    22. Leškowský, P., Cooke, T., Ernst, M. O., and Harders, M. 2006. Using multidimensional scaling to quantify the fidelity of haptic rendering of deformable objects. In Proceedings of the EuroHaptics 2006 International Conference (EH 2006).Google Scholar
    23. Misra, S., Fuernstahl, P., Ramesh, K., Okamura, A. M., and Harders, M. 2009. Quantifying perception of nonlinear elastic tissue models using multidimensional scaling. In EuroHaptics conference, 2009 and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. World Haptics 2009. Third Joint, IEEE, 570–575. Google ScholarDigital Library
    24. Morovic, J., and Luo, M. R. 2001. The fundamentals of gamut mapping: A survey. Journal of Imaging Science and Technology 45, 3, 283–290.Google Scholar
    25. Nisky, I., Pressman, A., Pugh, C. M., Mussa-Ivaldi, F. A., and Karniel, A. 2011. Perception and action in teleoperated needle insertion. Haptics, IEEE Transactions on 4, 3, 155–166. Google ScholarDigital Library
    26. Panetta, J., Zhou, Q., Malomo, L., Pietroni, N., Cignoni, P., and Zorin, D., 2015. Elastic textures for additive fabrication, aug. Julian Panetta and Quingnan Zhou are Joint first authors.Google Scholar
    27. Pellacini, F., Ferwerda, J. A., and Greenberg, D. P. 2000. Toward a psychophysically-based light reflection model for image synthesis. In Proceedings of the 27th annual conference on Computer graphics and interactive techniques, ACM Press/Addison-Wesley Publishing Co., 55–64. Google ScholarDigital Library
    28. Pressman, A., Welty, L. J., Karniel, A., and Mussa-Ivaldi, F. A. 2007. Perception of delayed stiffness. The International Journal of Robotics Research 26, 11-12, 1191–1203. Google ScholarDigital Library
    29. Pressman, A., Karniel, A., and Mussa-Ivaldi, F. A. 2011. How soft is that pillow? The perceptual localization of the hand and the haptic assessment of contact rigidity. The Journal of Neuroscience 31, 17, 6595–6604.Google ScholarCross Ref
    30. Reinhard, E., Heidrich, W., Debevec, P., Pattanaik, S., Ward, G., and Myszkowski, K. 2010. High dynamic range imaging: acquisition, display, and image-based lighting. Morgan Kaufmann. Google ScholarDigital Library
    31. Ren, Z., Yeh, H., Klatzky, R., and Lin, M. C. 2013. Auditory perception of geometry-invariant material properties. Visualization and Computer Graphics, IEEE Transactions on 19, 4, 557–566. Google ScholarDigital Library
    32. Schumacher, C., Bickel, B., Rys, J., Marschner, S., Daraio, C., and Gross, M. 2015. Microstructures to control elasticity in 3D printing. ACM Trans. Graph. 34, 4. Google ScholarDigital Library
    33. Sturm, J. 1999. Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones. Optimization Methods and Software 11–12, 625–653. Version 1.05 available from http://fewcal.kub.nl/sturm.Google Scholar
    34. Tan, H. Z., Pang, X. D., and Durlach, N. I. 1992. Manual resolution of length, force, and compliance. Advances in Robotics 42, 13–18.Google Scholar
    35. Tan, H. Z., Durlach, N. I., Shao, Y., and Wei, M. 1993. Manual resolution of compliance when work and force cues are minimized. ASME Dyn. Syst. Control Div. Publ. DSC, ASME, NEW YORK, NY,(USA), 1993, 49, 99–104.Google Scholar
    36. Tiest, W. M. B., and Kappers, A. M. 2009. Cues for haptic perception of compliance. Haptics, IEEE Transactions on 2, 4, 189–199. Google ScholarDigital Library
    37. Wills, J., Agarwal, S., Kriegman, D., and Belongie, S. 2009. Toward a perceptual space for gloss. ACM Transactions on Graphics 28, 4, 1–15. Google ScholarDigital Library
    38. Wu, W.-C., Basdogan, C., and Srinivasan, M. A. 1999. Visual, haptic, and bimodal perception of size and stiffness in virtual environments. ASME Dyn. Syst. Control Div. Publ. DSC 67, 19–26.Google Scholar
    39. Zhang, X., Le, X., Panotopoulou, A., Whiting, E., and Wang, C. C. L. 2015. Perceptual models of preference in 3D printing direction. ACM Trans. Graph. 34, 6 (Oct.), 215:1–215:12. Google ScholarDigital Library

ACM Digital Library Publication:


Overview Page: