Flat image recognition in the process of microdevice assembly

An image recognition system for use in the assembly of microdevices is developed. The system gives an increase in the assembly process precision. A pin-to-hole insertion task was used to test developed system. The system will be used for assembly of microring-based filters.

[1]  Gilles Burel,et al.  Vision feedback for SMD placement using neural networks , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[2]  Q.M.J. Wu,et al.  Intelligent 3-D sensing in automated manufacturing processes , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[3]  A. M. Madni,et al.  Microelectromechanical systems (MEMS): an overview of current state-of-the-art , 1998, 1998 IEEE Aerospace Conference Proceedings (Cat. No.98TH8339).

[4]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[5]  W. Trimmer.  Micromechanics and MEMS , 1997 .

[6]  Ulrich Rembold,et al.  An automated microrobot-based desktop station for micro assembly and handling of micro-objects , 1996, Proceedings 1996 IEEE Conference on Emerging Technologies and Factory Automation. ETFA '96.

[7]  Henrik Jakobsen,et al.  High volume production of silicon sensor microsystems for automotive applications , 1997 .

[8]  B. Tatyana,et al.  Application of neural classifier for flat image recognition in the process of microdevice assembly , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

[9]  Daniel E. Whitney,et al.  Quasi-Static Assembly of Compliantly Supported Rigid Parts , 1982 .

[10]  Hiroshi Sako,et al.  Handwritten digit recognition using state-of-the-art techniques , 2002, Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition.

[11]  D. S. Eddy,et al.  Application of MEMS technology in automotive sensors and actuators , 1998 .

[12]  Yoshio Yamamoto,et al.  Measurement of force sensory information for the automation of ultra-precision assembly tasks , 2001, 2001 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Proceedings (Cat. No.01TH8556).

[13]  J. Y. Kim,et al.  A vision based error-corrective algorithm for flexible parts assembly , 1999, Proceedings of the 1999 IEEE International Symposium on Assembly and Task Planning (ISATP'99) (Cat. No.99TH8470).

[14]  H. Kuwano.  MEMS for telecommunication systems , 1996, MHS'96 Proceedings of the Seventh International Symposium on Micro Machine and Human Science.

[15]  Richard W. Prager,et al.  The modified Kanerva model: theory and results for real-time word recognition , 1991 .

[16]  Tatiana Baidyk,et al.  Improved method of handwritten digit recognition tested on MNIST database , 2004, Image Vis. Comput..

[17]  Reymond Clavel,et al.  Issues in precision motion control and microhandling , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[18]  Ernst Kussul,et al.  Development of low-cost microequipment , 2002, Proceedings of 2002 International Symposium on Micromechatronics and Human Science.

[19]  Vladimir Vapnik,et al.  An overview of statistical learning theory , 1999, IEEE Trans. Neural Networks.

[20]  Isabelle Guyon,et al.  Comparison of classifier methods: a case study in handwritten digit recognition , 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

[21]  Yoshua Bengio,et al.  Gradient-based learning applied to document recognition , 1998, Proc. IEEE.

[22]  Dmitri A. Rachkovskij,et al.  Micromechanical engineering: a basis for the low-cost manufacturing of mechanical microdevices using microequipment , 1996 .

[23]  Jitendra Malik,et al.  Matching Shapes , 2001, ICCV.

[24]  Simon Haykin,et al.  GradientBased Learning Applied to Document Recognition , 2001 .

[25]  Seok Joo Lee,et al.  Recognizing and tracking of 3D-shaped micro parts using multiple visions for micromanipulation , 2001, MHS2001. Proceedings of 2001 International Symposium on Micromechatronics and Human Science (Cat. No.01TH8583).

[26]  Craig R. Friedrich,et al.  Development of the Micromilling Prolcess for High-Aspect-Ratio Microstructures , 1996 .

[27]  W. Trimmer.  Micromechanics and Mems Classic and Seminal Papers to 1990 , 1997 .

[28]  Ernst Kussul,et al.  Development of micromachine tool prototypes for microfactories , 2002 .

[29]  Ernst Kussul,et al.  Rosenblatt perceptrons for handwritten digit recognition , 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

[30]  Hyung Suck Cho,et al.  Visual sensor-based measurement for deformable peg-in-hole tasks , 1999, Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289).

[31]  T. N. Baidyk.  Application of flat image recognition technique for automation of micro device production , 2001, 2001 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Proceedings (Cat. No.01TH8556).

[32]  Tilo Pfeifer,et al.  Process observation for the assembly of hybrid micro systems , 2002, Proceedings of 2002 International Symposium on Micromechatronics and Human Science.

[33]  Tamio Tanikawa,et al.  Desktop Machining Microfactory , 2001 .

[34]  T. Pfeifer,et al.  Process observation for the assembly of hybrid micro systems , 2002 .