19.6.1 Factory Automation - General Vision Systems

Chapter Contents (Back)
Vision Systems, General. Automation, Systems.

PPT Vision,
WWW Link. Vendor, Inspection. Industrial Automation and Inspection systems.

WWW Link. Vendor, Inspection. Industrial Automation and Inspection systems. Eyebot.

Integral Vision,
WWW Link. Vendor, Inspection. Industrial Automation and Inspection systems. Especially flat panel display inspection systems.

Apt˙ra Machine Vision Solutions,
WWW Link. Vendor, Inspection. Industrial Automation, Assembly, Metrology, and Inspection systems.

Stemmer Imaging,
WWW Link. Vendor, Inspection. Europe based company. Cameras, hardware and software.

Voyant Vision,
WWW Link. Vendor, Inspection. Vendor, Transportation. Inspection and intelligent transportation systems.

Nitzan, D., and Rosen, C.A.,
Programmable Industrial Automation,
TC(25), No. 12, December 1976, pp. 1259-1270. BibRef 7612

Editor Introduction,
Robotics and Automation,
Computer(15), No. 12, December 1982, Special issue. Survey, Automation. Automation, Survey. Contains several survey type articles and 2 papers on robotics control and languages. BibRef 8212

Feddema, J.T., and Mitchell, O.R.,
Vision-Guided Servoing with Feature-Based Trajectory Generation,
RA(5), No. 5, October, 1989, pp. 691-700. BibRef 8910

Kak, A.C., Boyer, K.L., Chen, C.H., Safranek, R.J., and Yang, H.S.,
A Knowledge-Based Robotic Assembly Cell,
IEEE_EXPERT(1), Spring 1986, pp. 63-83.
PDF File. Sensory subsystem discussion, basically simple systems are used; e.g. structured light. See also Determination of the Identity, Position and Orientation of the Topmost Object in a Pile. and See also Color-Encoded Structured Light for Rapid Active Ranging. BibRef 8600

Nitzan, D.,
Three-Dimensional Vision Structure for Robot Applications,
PAMI(10), No. 3, May 1988, pp. 291-309.
IEEE DOI BibRef 8805

Muehlenfeld, E.,
Robot vision by a contour sensor with associative memory,
PR(17), No. 1, 1984, pp. 169-176.
Elsevier DOI 0309
the contour sensor recognizes and positions straight parts in arbitrary orientations on a conveyor belt. BibRef

Aylett, J.C., Fisher, R.B., Fothergill, A.P.,
Predictive Computer Vision for Robotic Assembly,
JIRS(1), 1988, pp. 185-201. BibRef 8800 Edinburgh BibRef

Aylett, J.C., Fisher, R.B., Fothergill, A.P.,
WPFM: The Workspace Prediction and Fast Matching System,
MRSC91(xx). BibRef 9100 Edinburgh BibRef

Mehrotra, R.[Rajiv], Kung, F.K.[Fu K.], Grosky, W.I.[William I.],
Industrial part recognition using a component-index,
IVC(8), No. 3, August 1990, pp. 225-232.
Elsevier DOI 0401

Ersu, E., Wienand, S.,
Vision System for Robot Guidance and Quality Measurement Systems in Automotive Industry,
IndRob(22), No. 6, 1995, pp. 26-29. BibRef 9500

Kolbl, W.,
Affordable Optical Seam Tracking: Metatorch Systems Break the Price Barrier,
IndRob(22), No. 6, 1995, pp. 19-21. BibRef 9500

Morris, J.,
M(2)Vip: Variety in Mechatronics and Vision,
IndRob(22), No. 6, 1995, pp. 16-18. BibRef 9500

Testa, J.,
The Vision-Guided Robot Grows Up: A Look at the New Machine Vision Technology for Robots,
IndRob(22), No. 6, 1995, pp. 13-15. BibRef 9500

Kolbl, W.,
Intelligent Vision Systems Are Set to Take-Off,
IndRob(22), No. 6, 1995, pp. 3-3. BibRef 9500

Park, T.H., Lee, B.H.,
Dynamic Tracking Line: Feasible Tracking Region of a Robot in Conveyor Systems,
SMC-B(27), No. 6, December 1997, pp. 1022-1030.
IEEE Top Reference. 9712

Kamel, M.[Mohamed], Padilha, J.[Jorge],
High performance computing for industrial visual inspection,
MVA(12), No. 4, 2000, pp. 157-157.
Springer DOI 0101
Special issue introduction. BibRef

Lux, A.[Augustin],
The Imalab Method for Vision Systems,
MVA(16), No. 1, December 2004, pp. 21-26.
Springer DOI 0501
Earlier: CVS03(314 ff).
Springer DOI 0306

Lux, A.[Augustin], and Souvignier, V.[Viviane],
PVV - A Goal-Oriented System for Industrial Vision,
IJCAI83(1121-1124). (Grenoble) The description module works bottom up constrained by the goal (find specific types of objects). Generate and test paradigm. BibRef 8300

Zou, X.J.[Xiang-Jun], Zou, H.X.[Hai-Xin], Lu, J.[Jun],
Virtual manipulator-based binocular stereo vision positioning system and errors modelling,
MVA(23), No. 1, January 2012, pp. 43-63.
WWW Link. 1201
Positioning tool. BibRef

Zhou, K.[Kai], Rooker, M.[Martijn], Akkaladevi, S.C.[Sharath Chandra], Fritz, G.[Gerald], Pichler, A.[Andreas],
How Industrial Robots Benefit from Affordances,
Springer DOI 1504

Eikvil, L.[Line], Holden, M.[Marit],
Evaluation of Binary Descriptors for Fast and Fully Automatic Identification,
Industrial sorting problem. Accuracy BibRef

Li, X.G.[Xian-Guo], Miao, C.Y.[Chang-Yun], Zhang, Y.[Yan],
A New Joint Detection Algorithm of Conveyer Belt X-Ray Imaging Using the BP Neural Networks,

Zemcik, P.[Pavel], Valenta, P.[Pavel], Honec, J.[Josef], Fucik, O.[Otto], and Richter, M.[Miloslav],
Visual Analysis On The Production Line,
HTML Version. 9705

Bachler, G.[Gernot], Berger, M.[Martin], R÷hrer, R.[Reinhard], Scherer, S.[Stefan], Pinz, A.[Axel],
A Vision Driven Automatic Assembly Unit,
Springer DOI 9909

Kitamura, Y., Sato, H., and Tamura, H.,
An Expert System for Industrial Machine Vision,
ICPR90(I: 771-774).
IEEE DOI BibRef 9000

Toriu, T., Goto, T., and Yoshida, M.,
An Investigation of Adaptable Vision System for Factory Automation,
CVPR85(222-224). (Fujitsu Laboratories Ltd.) A proposal for a decision tree learning system. BibRef 8500

Chapter on Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection continues in
Other Industrial Applications Areas .

Last update:Jun 14, 2018 at 16:13:32