1.Angulo V. R. and Torras C., “Speeding up the learning of robot kinematics through function decomposition,” IEEE Trans. Neural Networks 16 (6), 1504–1512 (Nov. 2005).
2.Barreto G. A., Araujo A. F. R. and Ritter H. J., “Self-organizing feature maps for modeling and control of robotic manipulators,” J. Intell. Rob. Syst. 36, 407–450 (2003).
3.Behera L. and Kirubanandan N., “A hybrid neural control scheme for visual-motor coordination,” IEEE Control Syst. Mag. 19 (4), 34–41 (1999).
4.Chaumette F., “Image moments: A general and useful set of features for visual servoing,” IEEE Trans. Rob. 20 (4), 713–723 (Aug. 2004).
5.Chaumette F. and Marchand E., “A redundancy-based iterative approach for avoiding joint limits: Application to visual servoing,” IEEE Trans. Rob. Automat. 17 (5), 719–730 (Oct. 2001).
6.Feddema J. T., George Lee C. S. and Mitchell O. W., “Weighted selection of image features for resolved rate visual feedback control,” IEEE Trans. Rob. Automat. 7 (1), 31–47 (Feb. 1991).
7.Han M., Okada N. and Kondo E., “Coordination of an uncalibrated 3-d visuo-motor system based on multiple self-organizing maps,” JSME Int. J. Ser. C 49 (1), 230–239 (2006).
8.Hutchinson S., Hager G. D. and Corke P. I., “A tutorial on visual servo control,” IEEE Trans. Rob. Automat. 12 (5), 651–670 (Oct. 1996).
9.Jiang P., Bamforth L. C. A., Feng Z., Baruch J. E. F. and Chen Y. Q., “Indirect iterative learning control for a discrete visual servo without a camera-robot model,” IEEE Trans. Syst. Man Cybernet. Part B: Cybernet. 37 (4), 863–876 (Aug. 2007).
10.Kohonen T., Self Organization and Associative Memory (Springer-Verlag, Berlin, Germany, 1984).
11.Kragic D. and Christensen H. I., Survey on Visual Servoing for Manipulation Technical Report (Stockholm, Sweden: Computational Vision and Active Perception Laboratory, KTH, 2002).
12.Kumar N. and Behera L., “Visual motor coordination using a quantum clustering based neural control scheme,” Neural Process. Lett. 20, 11–22 (2004).
13.Kumar S. and Behera L., “Implementation of a Neural Network Based Visual Motor Control Algorithm for a 7 dof Redundant Manipulator,” International Joint Conference on Neural Networks (IJCNN), Hong Kong, China (June 2008) pp. 1344–1351.
14.Kumar S., Patel N. and Behera L., “Visual motor control of a 7 dof robot manipulator using function decomposition and sub-clustering in configuration space,” Neural Process. Lett. 28 (1), 17–33 (Aug. 2008).
15.Li L., Gruver W. A., Zhang Q. and Yang Z., “Kinematic control of redundant robots and the motion optimizability measure,” IEEE Trans. Syst. Man Cybernet. Part B: Cybernet. 31 (1), 155–160 (Feb. 2001).
16.Li Y. and Leong S. H., “Kinematics control of redundant manipulators using a CMAC neural network combined with a genetic algorithm,” Robotica 22, 611–621 (2004).
17.Martinetz T., Ritter H. and Schulten K., “Learning of visuomotor-coordination of a robot arm with redundant degrees of freedom,” In Proceedings of the International Conference on Parallel Processing in Neural Systems and Computers (ICNC), (Elsevier, Dusseldorf and Amsterdam 1990) pp. 431–434.
18.Martinetz T. M., Ritter H. J. and Schulten K. J., “Three-dimensional neural net for learning visual motor coordination of a robot arm,” IEEE Trans. Neural Networks 1 (1), 131–136 (Mar. 1990).
19.Mayorgaa R. I. V. and Sanongboone P., “Inverse kinematics and geometrically bounded singularities prevention of redundant manipulators: An artificial neural network approach,” Rob. Auton. Syst. 53, 164–176 (2005).
20.Sharma R. and Hutchinson S., “Optimizing Hand/Eye Configuration for Visual-Servo Systems,” Proceedings of the International Conference on Robotics and Automation (ICRA), Nagoya, Japan (May 1995) pp. 172–177.
21.Spong M. W. and Vidyasagar M., Robot Dynamics and Control, New York, USA (John Wiley, 1989).
22.Tevatia G. and Schaal S., “Inverse Kinematics of Humanoid Robots.” Proceedings of the IEEE International Conference on Robotics and Automation, San Francisco, CA (Apr. 2000) pp. 294–299.
23.Tsai R. Y., “A versatile camera calibration technique for high-accuracy 3d machine vision metrology using off-the-shelf tv cameras and lenses,” IEEE J. Rob. Automat. RA-3 (4), 323–344 (Aug. 1987).
24.Walter J. A. and Schulten K. J., “Implementation of self-organizing neural networks for visual-motor control of an industrial robot,” IEEE Trans. Neural Networks 4 (1), 86–95 (Jan. 1993).
26.Xia Y. and Wang J., “A dual neural network for kinematic control of redundant robot manipulators,” IEEE Trans. Syst. Man Cybernet. Part B: Cybernet. 31 (1), 147–154 (Feb. 2001).
27.Zha H., Onitsuka T. and Nagata T., “A self-organization learning algorithm for visuo-motor coordination in unstructured environment,” Artif. Life Rob. 1 (3), 131–136 (Sep. 1997).
28.Zheng X.-Z. and Ito K., “Self-organized learning and its implementation of robot movements,” IEEE International Conference on SMC, “Computational Cybernetics and Simulation,” Orlando, FL (1997) pp. 281–286.