Machine vision approach for robotic assembly

Assembly Automation

Volumn 25, Issue 3, 2005, Pages 204-216

  Peña Cabrera, Mario ^a   Lopez Juarez, Ismael ^b   Rios Cabrera, Reyes ^b   Corona Castuera, Jorge ^b  

^a IIMAS UNAM   (Mexico)

^b Centro de Tecnologia Avanzada Mexico   (Mexico)

Author keywords

Assembly; Neural nets; Robotics

Indexed keywords

INDUSTRIAL ROBOTS; LEARNING SYSTEMS; NEURAL NETWORKS; OBJECT RECOGNITION; ROBOTIC ASSEMBLY; SENSORS;

BOUNDARY OBJECT FUNCTION (BOF); INTELLIGENT MANUFACTURING CELL; MULTIMODAL SENSOR; VISUAL PERCEPTION;

COMPUTER VISION;

EID: 26444487608     PISSN: 01445154     EISSN: None     Source Type: Trade Journal    
DOI: 10.1108/01445150510610926     Document Type: Article

References (48)

1. Aguado, A.S., Montiel, E. and Nixon, M. (2002), "Invariant characterization of the Hough transform for pose estimation of arbitrary shapes", Pattern Recognition, Vol. 35, pp. 1083-97.
2. Best, P.J. and McKay, N.D. (1992), "A method for registration of 3-D shapes", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 14 No. 2.
3. Bone, G.M. and Capson, D. (2003), "Vision-guided fixtureless assembly of automotive components", Robotics and Computer Integrated Manufacturing, Vol. 19, pp. 79-87.
4. Bribiesca, E. (1999), "A new chain code", Pattern Recognition, Vol. 32, pp. 235-51.
5. Carpenter, G.A. and Grossberg, S. (1987), "A massively parallel architecture for a self-organizing neural pattern recognition machine", Computer Vision, Graphics, and Image Processing, Vol. 37, pp. 54-115.
6. Carpenter, G.A., Grossberg, S. and Reynolds, J.H. (1991), " ARTMAP: Supervised real-time learning and classification of nonstationary data by self-organizing neural network", Neural Networks, Vol. 4, pp. 565-88.
7. Castuera, J.C. and López-Juárez, I. (2004), " Intelligent task level planning for robotic assembly: Issues and experiments", paper presented at the Mexican International Conferences on Artificial Intelligence, Springer-Verlag, New York, NY.
8. Chen, K. (1990), "Efficient parallel algorithms for computation of two-dimensional image moments", Pattern Recognition, Vol. 23, pp. 109-19.
9. Chin-Hsiung, Wu et al., (2001), "A new computation of shape moments via quadtree decomposition", Pattern Recognition, Vol. 34, pp. 1319-30.
10. Dickmanns, E. (1998), "Vehicles capable of dynamic vision: A new breed of technical beings?", Artifical Intelligence, Vol. 103, pp. 49-76.
11. Gupta, M.M. and Knopf, G. (1993), Neuro-Vision Systems: A Tutorial, a selected reprint, Volume IEEE, Neural Networks Council Sponsor, IEEE Press, New York, NY.
12. Gupta, M.M. and Knopf, G. (1993), Neuro-Vision Systems: Part 6 Computational Architectures and Applications, A selected reprint Volume IEEE Neural Networks Council Sponsor, IEEE Press, New York, NY.
13. Lopez-Juarez, I. and Howarth, M. (2000), "Learning, Manipulative Skills with ART", Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.
14. Peña-Cabrera, M. et al. (2004), "Un Proceso de Aprendizaje para Reconocimiento de Objetos en Línea en Tareas Robotizadas", 3ra Conferencia Iberoamericana en Sistemas, Cibernética e Informática CISCI, del 21 al 25 de julio del, Orlando, FL.
15. Vijaykumar, G., Franklin, J.A. and Benbrahim, H. (1994), " Acquiring robot skills via reinforcement learning", IEEE Control Systems, pp. 13-24.
16. Enric, Cervera and del pobil, A.P. (1997), "Programming and learning in real world manipulation tasks", Proceedings of the IEEE/RSJ International Conference on Intelligent Robot and Systems, pp. 471-6.
17. Feldman, R.S. (1993), Understanding Psychology, 3rd ed., McGraw-Hill, New York, NY.
18. Freeman, H. (1961), "On the encoding of arbitrary geometric configurations", IRE Trans. Electron. Comput., Vol. EC-10, pp. 260-8.
19. Freeman, H. (1974), "Computer processing of line drawings images", ACM Comput. Surveys, Vol. 6, pp. 57-97.
20. Gong, S. and Buxton, H. (2002), "Understanding visual behaviour", Image and Vision Computing, Vol. 20 No. 12, pp. 825-6.
21. Gonzalez-Galvan, E.J. et al., (1997), "Application of precision-enhancing measure in 3D rigid-body positioning using camera-space manipulation", The International Journal of Robotics Research, Vol. 16 No. 2, pp. 240-57.
22. Grossberg, S. (1976), "Adaptive pattern classification and universal recoding. II: Feedback, expectation, olfaction and illusions", Biological Cybernetics, Vol. 23, pp. 187-202.
23. Hager, G. et al. (1995), "Calibration-free visual control using projective invariance", Proceedings of the ICCV, pp. 1009-15.
24. Hoska, D.R. (1988), "Fixtureless assembly manufacturing", Manuf Eng., Vol. 100, pp. 49-54.
25. Howarth, M. (1998), "An investigation of task level programming for robotic assembly", PhD thesis, The Nottingham Trent University, Nottingham.
26. Hu, M.K. (1962), "Visual pattern recognition by moment invariants", IRE Trans. Inform. Theory, Vol. IT-8, pp. 179-87.
27. J̈rg, S. et al. (2000), "Flexible robot-assembly using a multi-sensory approach", Proceedings of the IEEE, International Conference on Robotics and Automation, San Francisco, CA, USA, pp. 3687-94.
28. Kollnig, H. and Nagel, H. (1997), "3D pose estimation by directly matching polyhedral models to gray value gradients", International Journal of Computer Vision, Vol. 23 No. 3, pp. 282-302.
29. Kronauer, R.E. and Zeevi, Y. (1985), "Reorganization and diversification of signals in vision", IEEE Trans. Syst. Man, Cybern., Vol. SMC-15 No. 1, pp. 91-101.
30. Langley, C.S. and D'Eleuterio, G.M.T. (2003), "A memory efficient neural network for robotic pose estimation", Proceedings of the 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation, Vol. 1, pp. 418-23.
31. Lopez-Juarez, I. (2000), "Online learning for robotic assembly using artificial neural networks and contact force sensing", PhD thesis, The Nottingham Trent University, Nottingham,.
32. Lin, J.C. (1996), "The family of universal axes", Pattern Recognition, Vol. 29 No. 3, pp. 477-85.
33. Murase, H. and Shree K., Nayar (1995), "Visual learning and recognition of 3-D objects from appearance", International Journal of Computer Vision, Vol. 14, pp. 5-24.
34. Ngyuen, W. and Mills, J.K. (1996), "Multirobot control for flexible fixtureless assembly of flexible sheet metal autobody parts", Proceedings of the IEEE International Conference on Robotics and Automation, pp. 2340-5.
35. Papanikolopoulous, N.P. and Khosla, K. (1993), "Adaptive robotic visual tracking: Theory and experiments", IEEE Transactions on Automatic Controller, Vol. 38 No. 3, pp. 429-45.
36. Peña-Cabrera, M. et al. (2004), "A learning approach for on-line object recognition in robotic tasks", paper presented at the Mexican International Conference on Computer Science ENC 2004, IEEE Computer Society Press, México.
37. Philips, W. (1993), "A new fast algorithm for moment computation", Pattern Recognition, Vol. 26, pp. 1619-21.
38. Plut, W.J. and Bone, G.M. (1996), "Limited mobility grasps for fixtureless assembly", Proceedings of the IEEE International Conference on Robotics and Automation, Minneapolis, MN, pp. 1465-70.
39. Plut, W.J. and Bone, G.M. (1997), "3-D flexible fixturing using multi-degree of freedom gripper for robotics fixtureless assembly", Proceedings of the IEEE International Conference on Robotics and Automation, Alburquerque, NM, pp. 379-84.
40. Stavros, J. and Lisboa, P. (1992), "Transltion, rotation, and scale invariant pattern recognition by high-order neural networks and moment classifiers", IEEE Transactions on Neural Networks, Vol. 3 No. 2.
41. Torralba, A. and Oliva, A. (2002), "Depth Estimation from Image Structure", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24 No. 9.
42. Towell, G.G. and Shavlik, J.W. (1994), "Knowledge-based artificial neural networks", Artificial Intelligence, Vol. 70 Nos 1/2, pp. 119-66.
43. Uhr, L. (1980), "Psychological motivation and underlying concepts", in Tanimoto, S. and Klinger, A. (Eds), Structured Computer Vision, pp. 1-30.
44. Underwood, S.A. et al., (1975), "Visual learning from multiple views", IEEE Transactions on Computers, Vol. c-24 No. 6.
45. Wu, L., Oviatt, S.L. and Cohen, P.R. (1999), "Multimodal integration - A statical view", IEEE Transactions on Multimedia, Vol. 1 No. 4, pp. 334-41.
46. Yüceer, C. and Oflazer, K. (1993), "A rotation, scaling and translation invariant pattern classification system", Pattern Recognition, Vol. 26 No. 5, pp. 687-710.
47. Yong-Sheng Chen et al., (2001), "Three dimensional ego-motion estimation from motion fields observed with multiple cameras", Pattern Recognition, Vol. 34, pp. 1573-83.
48. You, S.D. and Ford, G.E. (1994), "Network model for invariant object recognition", Pattern Recognition Letters, Vol. 15, pp. 761-7.