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3D Assembly Group Analysis for Cognitive Automation

DOI: 10.1155/2012/375642

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Abstract:

A concept that allows the cognitive automation of robotic assembly processes is introduced. An assembly cell comprised of two robots was designed to verify the concept. For the purpose of validation a customer-defined part group consisting of Hubelino bricks is assembled. One of the key aspects for this process is the verification of the assembly group. Hence a software component was designed that utilizes the Microsoft Kinect to perceive both depth and color data in the assembly area. This information is used to determine the current state of the assembly group and is compared to a CAD model for validation purposes. In order to efficiently resolve erroneous situations, the results are interactively accessible to a human expert. The implications for an industrial application are demonstrated by transferring the developed concepts to an assembly scenario for switch-cabinet systems. 1. Introduction One of the effects of globalization in public view is the reduction of production in high-wage countries especially due to job relocation abroad to low-wage countries, for example, towards Eastern Europe or Asia [1–3]. Based on this, a competition between manufacturing companies in high-wage and low-wage countries typically occurs within two dimensions: value-orientation and planning-orientation. Possible disadvantages of production in low-wage countries concerning process times, factor consumption and process mastering are compensated by low productive factor costs. In contrast, companies in high-wage countries try to utilize the relatively expensive productivity factors by maximizing the output (economies of scale). Another way to compensate the arising unit cost disadvantages is customization or fast adaptation to market needs (economies of scope), even though the escape into sophisticated niche markets does not seem to be a promising way for the future anymore. Within the dimension planning-orientation companies in high-wage countries try to optimize processes with sophisticated, investment-intensive planning approaches, and production systems while value-orientation offers the benefit of shop floor-oriented production with little planning effort. Since processes and production systems do not exceed the limits of an optimal operating range, additional competitive disadvantages for high-wage countries emerge. In order to achieve a sustainable competitive advantage for manufacturing companies in high-wage countries with their highly skilled workers, it is therefore not promising to further increase the planning orientation of the manufacturing systems and

References

[1]  E. von Weizs?cker, Globalisierung der Weltwirtschaft - Herausforderungen und Antworten, vol. 5 of Politik und Zeitgeschichte, 2003, http://www.bpb.de/publikationen/U27MV5,0,Globalisierung_der_Weltwirtschaft_Herausforderungen_und_Antworten.html.
[2]  DIHK, “Produktionsverlagerung als Element der Globalisierungsstrategie von Unternehmen: Ergebnisse einer Unternehmensbefragung,” 2011, http://www.dihk.de/ressourcen/downloads/produktionsverlagerung.pdf.
[3]  DIHK, “Auslandsinvestitionen in der Industrie,” 2011, http://www.muenchen.ihk.de/mike/ihk_geschaeftsfelder/starthilfe/Anhaenge/DIHK-Auslandsinvestitionen-2010.pdf.
[4]  F. Klocke, “Production technology in high-wage countries: from ideas of today to products of tomorrow,” in Industrial Engineering and Ergonomics: Visions, Concepts, Methods and Tools, C. Schlick, Ed., Festschrift in Honor of Professor Holger Luczak, Springer, New York, NY, USA, 2009.
[5]  S. Kinkel, Arbeiten in der Zukunft: Strukturen und Trends der Industriearbeit, Ed. Sigma, Berlin, Germany, 2008.
[6]  L. Bainbridge, “Ironies of automation,” in New Technology and Human Error, J. Rasmussen, K. Duncan, and J. Leplat, Eds., pp. 775–779, John Wiley & Sons, Chichester, UK, 1987.
[7]  R. Onken and A. Schulte, System-Ergonomic Design of Cognitive Automation: Dual-Mode Cognitive Design of Vehicle Guidance and Control Work Systems, Springer, Berlin, Germany, 2010.
[8]  C. Brecher, Ed., Integrative Produktionstechnik für Hochlohnl?nder, Springer, Berlin, Germany, 2011.
[9]  M. F. Z?h, M. Beetz, K. Shea, et al., “The cognitive factory,” in Changeable and Reconfigurable Manufacturing Systems, H. A. El-Maraghy, Ed., Springer, Berlin, Germany, 2009.
[10]  S. Karim, L. Sonenberg, and A. H. Tan, “A hybrid architecture combining reactive plan execution and reactive learning,” in Proceedings of the 9th Biennial Pacific Rim International Conference on Artificial Intelligence (PRICAI '06), China, 2006.
[11]  E. Gat, “On three-layer architectures,” in Artificial Intelligence and Mobile Robots, D. Kortenkamp, R. Bonnasso, and R. Murphy, Eds., pp. 195–211, AAAI Press, Menlo Park, Calif, USA, 1998.
[12]  S. J. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, Pearson Education, Upper Saddle River, NJ, USA, 2003.
[13]  K. Paetzold, “On the importance of a functional description for the development of cognitive technical systems,” in International Design Conference, Dubrovnik, Croatia, 2006.
[14]  P. Adelt, J. Donath, J. Gausemeier, et al., “Selbstoptimierende Systeme des Maschinenbaus,” in HNI-Verlagsschriftenreihe, J. Gausemeier, F. Rammig, and W. Sch?fer, Eds., Westfalia Druck GmbH, Paderborn, Germany, 2009.
[15]  M. Z?h and M. Wiesbeck, “A model for adaptively generating assembly instructions using state-based graphs,” in Manufacturing Systems and Technologies for the New Frontier, The 41st CIRP Conference on Manufacturing Systems, Tokyo, Japan, 2008.
[16]  M. Z?h, M. Wiesbeck, F. Engstler, et al., “Kognitive Assistenzsysteme in der manuellen Montage,” in wt Werkstatttechnik, vol. 97, no. 9, pp. 644–650, 2007.
[17]  H. Ding, S. Kain, F. Schiller, and O. A. Stursberg, “Control architecture for safe cognitive systems,” in 10. Fachtagung Entwurf komplexer Automatisierungssysteme, Magdeburg, Germany, 2008.
[18]  S. Kammel, J. Ziegler, B. Pitzer et al., “Team AnnieWAY's autonomous system for the 2007 DARPA Urban Challenge,” Journal of Field Robotics, vol. 25, no. 9, pp. 615–639, 2008.
[19]  H. J. Putzer, Ein uniformer Architekturansatz für Kognitive Systeme und seine Umsetzung in ein operatives Framework, Dr. K?ster, Berlin, Germany, 2004.
[20]  D. Ewert, E. Hauck, A. Gramatke, and S. Jeschke, “Cognitive assembly planning using state graphs,” in Proceedings of the 3rd International Conference on Applied Human Factors and Ergonomics, Miami, Fla, USA, 2010.
[21]  T. Kempf, W. Herfs, and C. Brecher, “Cognitive Control Technology for a Self-optimizing Robot Based Assembly Cell,” in ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conferences (DETC '08), New York, NY, USA, August 2008.
[22]  M. Mayer, B. Odenthal, M. Faber, et al., “Cognitive engineering for direct human-robot cooperation in self-optimizing assembly cells,” in First International Conference on Human Centered Design (HCD '09), M. Kurosu, Ed., San Diego, Calif, USA, July 2009.
[23]  C. Schlick, B. Odenthal, M. Mayer, et al., “Design and evaluation of an augmented vision system for self-optimizing assembly cells,” in Industrial Engineering and Ergonomics: Visions, Concepts, Methods and Tools, C. Schlick, Ed., Festschrift in Honor of Professor Holger Luczak, Springer, New York, NY, USA, 2009.
[24]  T. B. Sheridan, Humans and Automation: System Design and Research Issues, Human Factors and Ergonomics Soc, Santa Monica, Calif, USA, 2001.
[25]  M. Mayer, B. Odenthal, and M. Grandt, “Task-oriented process planning for cognitive production systems using MTM,” in Proceedings of the 2nd International Conference on Applied Human Factors and Ergonomic, Louisville, Ky, USA, 2008.
[26]  V. Gazzola, G. Rizzolatti, B. Wicker, and C. Keysers, “The anthropomorphic brain: the mirror neuron system responds to human and robotic actions,” NeuroImage, vol. 35, no. 4, pp. 1674–1684, 2007.
[27]  E. Drumwright, “Toward a vocabulary of primitive task programs for humanoid robots,” in Proceedings of the International Conference on Development and Learning (ICDL '06), Bloomington, Ind, USA, 2006.
[28]  B. Odenthal, M. Mayer, N. Jochems, and C. Schlick, “Cognitive engineering for human-robot interaction—the effect of subassemblies on assembly strategies,” in Advances in Human Factors, Ergonomics, and Safety in Manufacturing and Service Industries, pp. 1–10, CRC Press, Boca Raton, Fla, USA, 2011.
[29]  M. Mayer, C. Schlick, D. Ewert et al., “Automation of robotic assembly processes on the basis of an architecture of human cognition,” Production Engineering Research and Development, vol. 5, no. 4, pp. 423–431, 2011.
[30]  T. Kempf, Ein kognitives Steuerungsframework für robotergestützte Handhabungsaufgaben, Apprimus, Aachen, Germany, 1st edition, 2010.
[31]  B. Odenthal, M. Mayer, W. Kabu?, B. Kausch, and C. Schlick, “Investigation of error detection in assembled workpieces using an augmented vision system,” in Proceedings of the 17th World Congress on Ergonomics (IEA '09), Beijing, China, August 2009.
[32]  B. Odenthal, M. Mayer, W. Kabu?, and C. Schlick, “Einfluss der Bildschirmposition auf die Fehlererkennung in einem Montagebautei,” in Neue Arbeits- und Lebenswelten gestalten: Vom 24. - 26. M?rz, M. Schütte, Ed., pp. 203–206, GfA-Press, Dortmund, Germany, 2010.
[33]  B. Odenthal, M. Mayer, W. Kabu?, B. Kausch, and C. Schlick, “An empirical study of disassembling using an augmented vision system,” in 3rd International Conference on Digital Human Modeling (ICDHM '11), Orlando, Fla, USA, 2011.
[34]  C. Beder, B. Bartczak, and R. Koch, “A comparison of PMD-cameras and stereo-vision for the task of surface reconstruction using patchlets,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '07), June 2007.
[35]  C. Sa, “Time of Flight Camera Technology,” Technology, 2009.
[36]  D. Schauer, Integration of a 3D time of flight camera system into a robot system: integration, validation and comparison, VDM Verlag Dr. Müller, Saarbrücken, Germany, 2011.
[37]  Microsoft, Ed, “Programming Guide: Getting Started with the Kinect for Windows SDK Beta from Microsoft Research,” 2011.
[38]  D. Laing, “Kinect - Could this technology have a future in industrial automation?” http://blog.vdcresearch.com/industrial_automation/2010/11/kinect-could-this-technology-have-a-future-in-industrial-automation.html.
[39]  D. L. Andrews, Structured light and its applications: an introduction to phase-structured beams and nanoscale optical forces, Academic Press, Amsterdam, The Netherlands, 2008.
[40]  Z. Song, Use of structured light for 3D reconstruction, Hong Kong, 2008.
[41]  K. Clague and M. Agullo, LEGO software power tools, Syngress, Rockland, Mass, USA, 2002.
[42]  Z. Yaniv, “Random Sample Consensus (RANSAC) Algorithm, A Generic Implementation,” Information Systems Journal, 2010, http://isiswiki.georgetown.edu/zivy/writtenMaterial/RANSAC.pdf.
[43]  R. Szeliski, “Computer vision: Algorithms and applications,” Computer Vision, 2011, http://www.worldcat.org/oclc/700473658.
[44]  C. Stephens, “Lego Color List - official names, numbers, CYMK, RGB, Pantone values,” 2011, http://isodomos.com/Color-Tree/Lego-List.html.
[45]  C. Zhang, N. Xi, and Q. Shi, “Object-orientated registration method for surface inspection of automotive windshields,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '08), pp. 3553–3558, September 2008.
[46]  X. Liang, J. Liang, J. Liu, and C. Guo, “A rapid inspection method for large water turbine blade,” in IEEE International Conference on Mechatronics and Automation (ICMA '10), pp. 712–716, August 2010.
[47]  F. Bosché, “Automated recognition of 3D CAD model objects in laser scans and calculation of as-built dimensions for dimensional compliance control in construction,” Advanced Engineering Informatics, vol. 24, no. 1, pp. 107–118, 2010.
[48]  L. Yue and X. Liu, “Application of 3D optical measurement system on quality inspection of turbine blade,” in 16th IEEE International Conference on Industrial Engineering and Engineering Management (IE and EM '09), pp. 1089–1092, October 2009.
[49]  A. Tellaeche, R. Arana, A. Ibarguren, and J. Martínez-Otzeta, “Automatic quality inspection of percussion cap mass production by means of 3D machine vision and machine learning techniques,” in Lecture Notes in Computer Science, Hybrid Artificial Intelligence Systems, M. Gra?a Romay, E. Corchado, and M. Garcia Sebastian, Eds., pp. 270–277, Springer, Berlin, Germany, 2010.
[50]  B. Muralikrishnan and J. Raja, Computational Surface and Roundness Metrology, Springer, 2009.

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