A Smart System for Haptic Quality Control: A Knowledge-Based Approach to Formalize the Sense of Touch
Conference paper
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Abstract
The field of quality control has seen over the last decades a variety of studies and innovations turned towards the improvement of the perceptions rendered through manufactured products. Thus, quality checks do not only rely on technical control, but on a diversity of controls which correspond to the senses involved when interacting with a product. However, the quality specifications and in particular the vocabulary used for their description are still very specific to each product or industrial domain. With the perspective of simplifying and standardizing perceived quality control, this study aims at providing a Smart System based on knowledge modelling methods which is capable of guiding manufacturers in the process of structuring, generalizing and eventually automatizing the control process related to perceived quality and touch in particular. This paper presents a general framework for the Smart System as well as an ontological structure for the representation of perceived quality knowledge. The specificities of the sense of touch are detailed and led to the proposition of novel formalized description and conceptual model of haptic perceptions.
Keywords
Sensory perception Haptics Smart system Semantic analysis Quality control Perceived qualityNotes
Acknowledgments
This work has been done within a thesis project funded by the French technological research association (ANRT) as well as the company INEVA (INEVA: http://www.ineva.fr/). This work is the result of a collaboration between three parties, which are all acknowledged here: the company INEVA, the INSA de Strasbourg (with the ICube laboratory) and the University of Savoie Mont Blanc (with the SYMME laboratory).
References
- 1.Katz, D.: The World of Touch. Psychology Press, New York (2013)CrossRefGoogle Scholar
- 2.Lederman, S., Klatzky, R.L.: Haptic perception: a tutorial. Atten. Percept. Psychophys. 71, 1439–1459 (2009)CrossRefGoogle Scholar
- 3.Zanni-Merk, C.: KREM: a generic knowledge-based framework for problem solving in engineering - proposal and case studies. In: INSTICC (eds.) 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, pp. 381–388. Science and Technology Publications, Lda (2015)Google Scholar
- 4.Zanni-Merk, C., Marc-Zwecker, S., Wemmert, C., de Beuvron, B.F.: A layered architecture for a fuzzy semantic approach for satellite image analysis. Int. J. Knowl. Syst. Sci. 6, 31–56 (2015)CrossRefGoogle Scholar
- 5.Gartiser, N., Zanni-Merk, C., Boullosa, L., Casali, A.: A semantic layered architecture for analysis and diagnosis of SME. Procedia Comput. Sci. 35, 1165–1174 (2014). https://doi.org/10.1016/j.procs.2014.08.212. Elsevier Masson SASCrossRefGoogle Scholar
- 6.Milton, N.: Knowledge Technologies. Polimetrica, Milano (2008)Google Scholar
- 7.Sanín, C., Szczerbicki, E.: Experience-based knowledge representation: SOEKS. Cybern. Syst. 40, 99–122 (2009)CrossRefGoogle Scholar
- 8.Aamodt, A., Plaza, E.: Case-based reasoning: foundational issues, methodological variations, and system approaches. AI Commun. 7, 39–59 (1994)Google Scholar
- 9.Dey, A.K., Abowd, G.D., Salber, D.: A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Hum.-Comput. Interact. 16, 97–166 (2001)CrossRefGoogle Scholar
- 10.Compton, M., et al.: The SSN ontology of the W3C semantic sensor network incubator group. J. Semant. 17, 25–32 (2012)CrossRefGoogle Scholar
- 11.DOLCE+DnS\_Ultralite (2010). ontologydesignpatterns.org
- 12.Albert, B., et al.: A smart system for haptic quality control - introducing an ontological representation of sensory perception knowledge. In: Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, Porto. SCITEPRESS - Science and Technology Publications, pp. 21–30 (2016)Google Scholar
- 13.Roussey, C., Pinet, F., Kang, M.A., Corcho, O.: An introduction to ontologies and ontology engineering. In: Falquet, G., Métral, C., Teller, J., Tweed, C. (eds.) Ontologies in Urban Development Projects. AI&KP, vol. 1, pp. 9–38. Springer, London (2011). https://doi.org/10.1007/978-0-85729-724-2_2CrossRefGoogle Scholar
- 14.Hayward, V.: Is there a ‘plenhaptic’ function? Philos. Trans. Royal Soc. B: Biol. Sci. 366, 3115–3122 (2011)CrossRefGoogle Scholar
- 15.Albert, B., et al.: Generic and structured description of tactile sensory perceptions. In: KEER, Number September, Leeds, UK (2016)Google Scholar
- 16.Albert, B., et al.: Formalisation du Contrôle Qualité Haptique: Structuration Sémantique des Sensations Haptiques. IC (2016)Google Scholar
- 17.De Boissieu, F.: Toucher artificiel à base d’un microcapteur d’effort: traitement du signal et des informations associées. Ph.D. thesis, Université de Grenoble (2010)Google Scholar
- 18.De Rossi, D., Scilingo, E.P.: Skin-like sensor arrays. Encycl. Sens. 10, 1–22 (2006)Google Scholar
- 19.Purves, D., et al.: Neuroscience, 2nd edn. Sinauer Associates, Sunderland (2001)Google Scholar
- 20.Crochemore, S., Vergneault, C., Nesa, D.: A new reference frame for tactile perceptions: sensotact. 5th Rose Mary Pangborn, Boston, MA, USA, pp. 20–24 (2003)Google Scholar
- 21.Issa, M., Schacher, L., Adolphe, D.C.: Invariant attributes in the tactile characterization of fabrics. In: Proceeding of the Fiber Society Spring Conference (2005)Google Scholar
- 22.Picard, D., Dacremont, C., Valentin, D., Giboreau, A.: Perceptual dimensions of tactile textures. Acta Psychol. 114, 165–184 (2003)CrossRefGoogle Scholar
- 23.Sola, C.: Y a pas de mots pour le dire, il faut sentir: Décrire et dénommer les happerceptions professionnelles. Terrain (2007)Google Scholar
- 24.Summers, I.R., Irwin, R.J., Brady, A.C.: Haptic discrimination of paper. In: Human Haptic Perception: Basics and Applications, Number December 2007, pp. 525–535. Birkhäuser Basel (2007)Google Scholar
- 25.Dumenil-Lefebvre, A.: Integration Des Aspects Sensoriels Dans La Conception Des Emballages En Verre: Mise Au Point D’Un Instrument Methodologique À Partir Des Techniques D’Evaluation Sensorielle. Ph.D. thesis, Ecole nationale supérieure d’arts et métiers (2006)Google Scholar
- 26.Baudet, N.: Maîtrise de la qualité visuelle des produits - Formalisation du processus d’expertise et proposition d’une approche robuste de contrôle visuel humain. Ph.D. thesis, Université de Grenoble (2012)Google Scholar
- 27.Maire, J.L., Pillet, M., Baudet, N.: Measurement of the perceived quality of a product - characterization of aesthetic anomalies. Int. J. Metrol. Qual. Eng. 4, 63–69 (2013)CrossRefGoogle Scholar
- 28.Bassereau, J.F., Charvet-Pello, R.: Dictionnaire des mots du sensoriel. Lavoisier (2011)Google Scholar
- 29.Martin, S., Brown, W.M., Klavans, R., Boyack, K.W.: OpenOrd: an open-source toolbox for large graph layout. In: Proceedings of the SPIE, vol. 7868, pp. 786806–786811 (2011)Google Scholar
- 30.Bensmaïa, S., Hollins, M.: Pacinian representations of fine surface texture. Percept. Psychophys. 67, 842–854 (2005)CrossRefGoogle Scholar
- 31.Jones, L.A., Lederman, S.J.: Human Hand Function. Oxford University Press, Oxford (2006)CrossRefGoogle Scholar
- 32.Hatwell, Y., Streri, A., Gentaz, E.: Touch for Knowing. John Benjamins, Amsterdam (2003)CrossRefGoogle Scholar
- 33.Myrgioti, E., Bassiliades, N., Miliou, A.: Bridging the HASM: an OWL ontology for modeling the information pathways in haptic interfaces software. Expert Syst. Appl. 40, 1358–1371 (2013)CrossRefGoogle Scholar
- 34.Bārzdiņš, J., Bārzdiņš, G., Čerāns, K., Liepiņš, R., Sprog̀is, A.: UML style graphical notation and editor for OWL 2. In: Forbrig, P., Günther, H. (eds.) BIR 2010. LNBIP, vol. 64, pp. 102–114. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-16101-8_9CrossRefGoogle Scholar
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