An objective quality evaluation method for haptic rendering system: taking hardness rendering as an example

• Autorzy: Shao Zhiyu , Wu Juan , Ouyang Qiangqiang

Identyfikatory

DOI

10.24425/mms.2019.129579

• Języki publikacji: EN

Abstrakty

EN

Quality evaluation is very important for haptic rendering. In this paper, an objective evaluation method for a haptic rendering system based on haptic perception features is proposed. In the method, the haptic rendering process is compared to the real world perception process in a simple standardized procedure based on feature extraction and data analysis. A complete evaluation process for a simple haptic rendering task of pressing a virtual spring is presented as an example to explain the method in detail. Compared with the traditional objective method based on error statistics, the method is more concerned about the consistency of human subjective feelings rather than physical parameters, which makes the evaluation process more consistent with the haptic perception mechanism. The results of comparative analysis show that the method presented in this paper is simple, gives reliable results reflecting the consistency with subjective feeling and has a better discrimination ability for different kinds of devices and algorithms compared with the traditional evaluation methods.

Słowa kluczowe

EN

haptic rendering evaluation; human-machine interaction; haptic perception; measurement method; quality evaluation; bionic method

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2019
• Tom: Vol. 26, nr 3
• Strony: 475--496
• Opis fizyczny: Bibliogr. 48 poz., rys., tab., wykr., wzory

Twórcy

autor

Shao Zhiyu

• Southeast University, National Key Laboratory for Bioelectronics, Robotic Sensor and Control Laboratory, 2, Sipailou, Nanjing, China

autor

Wu Juan

• Southeast University, National Key Laboratory for Bioelectronics, Robotic Sensor and Control Laboratory, 2, Sipailou, Nanjing, China

autor

Ouyang Qiangqiang

• Southeast University, National Key Laboratory for Bioelectronics, Robotic Sensor and Control Laboratory, 2, Sipailou, Nanjing, China

Bibliografia

• [1] Brooks, T.L. (1990). Telerobotic response requirements. Systems, Man and Cybernetics, 1990. Conference Proceedings, IEEE International Conference, 113-120.
• [2] McAffee, D.A., Fiorini, P. (1991). Hand controller design requirements and performance issues intelerobotics. Advanced Robotics, 1991. ’Robots in Unstructured Environments’, 91 ICAR., Fifth International Conference, 186-192.
• [3] Hunter, I.W., Hollerbach, J.M., Ballantyne, J. (1991). A comparative analysis of actuator technologies for robotics. Robotics Review, 2, 299-342.
• [4] Hayward, V., Astley, O.R. (1996). Performance measures for haptic interfaces. Robotics research, London, Springer, 195-2016.
• [5] Colgate, J.E., Brown, J.M. (1994). Factors affecting the z-width of a haptic display. Robotics and Automation, Proc., 3205-3210.
• [6] Wu, J., Ding, Y., Ni, D., Song, G., Liu, W. (2013). Vibrotactile representation of three-dimensional shape and implementation on a vibrotactile pad. Sensors and Materials, 25(1), 79-97.
• [7] Kim, U., Kang, J., Lee, C., Kwon, H.Y., Hwang, S., Moon, H., Choi, H.R. (2013). A transparent and stretchable graphene-based actuator for tactile display. Nanotechnology, 24(14), 145501.
• [8] Shang, W., Su, H., Li, G., Fischer, G.S. (2013). Teleoperation system with hybrid pneumatic-piezoelectric actuation for MRI-guided needle insertion with haptic feedback. Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference, 4092-4098.
• [9] Chen, D., Song, A., Tian, L. (2015). A novel miniature multi-mode haptic pen for image interaction on mobile terminal. Haptic, Audio and Visual Environments and Games (HAVE), 2015 IEEE International Symposium, 1-6.
• [10] Hayward, V., Armstrong, B. (2000). A new computational model of friction applied to haptic rendering. Experimental Robotics VI, Springer, London, 403-412.
• [11] Kim, S.Y., Park, J., Kwon, D.S. (2005). The real-time haptic simulation of a biomedical volumetric object with shape-retaining chain linked model. IEICE transactions on information and systems, 88(5), 1012-1020.
• [12] Lang, J., Andrews, S. (2011). Measurement-based modeling of contact forces and textures for haptic rendering. IEEE Transactions on Visualization and Computer Graphics, 17(3), 380-391.
• [13] Samur, E., Wang, F., Spaelter, U., Bleuler, H. (2007). Generic and systematic evaluation of haptic interfaces based on testbeds. 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’07), 2113-2119.
• [14] Kirkpatrick, A.E., Douglas, S.A. (2002). Application-based evaluation of haptic interfaces. Haptic Interfaces for Virtual Environment and Teleoperator Systems, HAPTICS 2002, 32-39.
• [15] Kocsis, M.B., Cholewiak, S.A., Traylor, R.M., Adelstein, B.D., Hirleman, E.D., Tan, H.Z. (2013). Discrimination of real and virtual surfaces with sinusoidal and triangular gratings using the fingertip and stylus. IEEE transactions on haptics, 6(2), 181-192.
• [16] Okamura, A.M., Webster, R.J., Nolin, J.T., Johnson, K.W., Jafry, H. (2003). The haptic scissors: Cutting in virtual environments. IEEE International Conference on Robotics and Automation, 1, 828-833.
• [17] Kuchenbecker, K.J., Fiene, J., Niemeyer, G. (2005). Event-based haptics and acceleration matching: Portraying and assessing the realism of contact. Eurohaptics Conference, 2005 and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, World Haptics 2005. First Joint, 381-387.
• [18] Leškovský, P., Cooke, T., Ernst, M., Harders, M. (2006). Using multidimensional scaling to quantify the fidelity of haptic rendering of deformable objects. Proc. of EUROHAPTICS, 289-295.
• [19] Ruffaldi, E., Morris, D., Edmunds, T., Barbagli, F., Pai, D.K. (2006). Standardized evaluation of haptic rendering systems. Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2006 14th Symposium, 225-232.
• [20] Swindells, C., MacLean, K.E., Booth, K.S. (2009). Designing for feel: Contrasts between human and automated parametric capture of knob physics. IEEE transactions on haptics, 2(4), 200-211.
• [21] Hassen, R., Steinbach, E. (2018). HSSIM: An Objective Haptic Quality Assessment Measure for Force-Feedback Signals. Tenth International Conference on Quality of Multimedia Experience (QoMEX), 1-6.
• [22] Amari, S. (2003).The handbook of brain theory and neural networks. MIT Press.
• [23] Rivers, W.H.R. (1894). A modification of aristotle’s experiment. Mind, 3(12), 583-b.
• [24] Geldard, F.A., Sherrick, C.E. (1972). The cutaneous “rabbit”: a perceptual illusion. Science, 178(4057), 178-179.
• [25] Helson, H., King, S.M. (1931). The tau effect: an example of psychological relativity. Journal of Experimental Psychology, 14(3), 202.
• [26] Price-Williams, D.R. (1954). The kappa effect. Nature, 173(4399), 363.
• [27] Harris, J.A., Miniussi, C., Harris, I.M., Diamond, M.E. (2002). Transient storage of a tactile memory trace in primary somatosensory cortex. Journal of Neuroscience, 22(19), 8720-8725.
• [28] Dinse, H.R., Kalisch, T., Ragert, P., Pleger, B., Schwenkreis, P., Tegenthoff, M. (2005). Improving human haptic performance in normal and impaired human populations through unattended activation-based learning. ACM Transactions on Applied Perception (TAP), 2(2), 71-88.
• [29] Repperger, D.W., Phillips, C.A., Berlin, J.E., Neidhard-Doll, A.T., Haas, M.W. (2005). Human-machine haptic interface design using stochastic resonance methods. IEEE Transactions on systems, man, and cybernetics-part A: Systems and Humans, 35(4), 574-582.
• [30] Goldreich, D. (2007). A Bayesian perceptual model replicates the cutaneous rabbit and other tactile spatiotemporal illusions. PloS one, 2(3), 333.
• [31] Stevens, S.S. (1957). On the psychophysical law. Psychological review, 64(3), 153.
• [32] Han, G., Choi, S. (2010). Extended rate-hardness: a measure for perceived hardness. International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, 117-124.
• [33] Salton, G., Wong, A., Yang, C.S. (1975). A vector space model for automatic indexing. Communications of the ACM, 18(11), 613-620.
• [34] Chaudhari, R., Steinbach, E., Hirche, S. (2011). Towards an objective quality evaluation framework for haptic data reduction. 2011 IEEE World Haptics Conference, 539-544.
• [35] Hassen, R., Steinbach, E. (2018). HSSIM: An objective haptic quality assessment measure for force-feedback signals. 2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX), 1-6.
• [36] Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P. (2004). Image quality assessment: from error visibility to structural similarity. IEEE transactions on image processing, 13(4), 600-612.
• [37] Tiest, W.M.B., Kappers, A.M. (2009). Cues for haptic perception of compliance. IEEE Transactions on Haptics, 2(4), 189-199.
• [38] Hinterseer, P., Hirche, S., Chaudhuri, S., Steinbach, E., Buss, M. (2008). Perception-based data reduction and transmission of haptic data in telepresence and teleaction systems. IEEE Transactions on Signal Processing, 56(2), 588-597.
• [39] Nadjarbashi, O.F., Abdi, H., Nahavandi, S. (2015). Applying inverse just-noticeable-differences of velocity to position data for haptic data reduction. Systems, Man, and Cybernetics (SMC), 2015 IEEE International Conference, 440-445.
• [40] Jones, L.A. (2000). Kinesthetic sensing. Human and Machine Haptics.
• [41] Pang, X.D., Tan, H.Z., Durlach, N.I. (1991). Manual discrimination of force using active finger motion. Perception & Psychophysics, 49(6), 531-540.
• [42] Jones, L.A., Hunter, I.W. (1990). Influence of the mechanical properties of a manipulandum on human operator dynamics. Biological Cybernetics, 62(4), 299-307.
• [43] Partridge, L.D. (1966). Signal-handling characteristics of load-moving skeletal muscle. American Journal of Physiology-Legacy Content, 210(5), 1178-1191.
• [44] Kammerl, J., Chaudhari, R., Steinbach, E. (2011). Combining contact models with perceptual data reduction for efficient haptic data communication in networked VEs. IEEE Transactions on Instrumentation and Measurement, 60(1), 57-68.
• [45] Ambrosi, G., Bicchi, A., De Rossi, D., Scilingo, E.P. (1999). The role of contact area spread rate in haptic discrimination of softness. Robotics and Automation, 1999 IEEE International Conference, 1, 305-310. IEEE.
• [46] Lawrence, D.A., Pao, L.Y., Dougherty, A.M., Salada, M.A., Pavlou, Y. (2000). Rate-hardness: A new performance metric for haptic interfaces. IEEE Transactions on Robotics and Automation, 16(4), 357-371.
• [47] Mastmeyer, A., Hecht, T., Fortmeier, D., Handels, H. (2014). Ray-casting based evaluation framework for haptic force feedback during percutaneous transhepatic catheter drainage punctures. International Journal of Computer Assisted Radiology and Surgery, 9(3), 421-431.
• [48] Mastmeyer, A., Fortmeier, D., Handels, H. (2017). Evaluation of direct haptic 4d volume rendering of partially segmented data for liver puncture simulation. Scientific reports, 7(1), 671.

Uwagi

EN

1. This research was supported by National Natural Science Foundation of China under grants 61473088, National Key Laboratory for Bioelectronics and Jiangsu Key Laboratory for Remote Measurement and Control. The authors acknowledge Professor Hong Z. Tan from Purdue University for her advice to this paper.

PL

2. Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).