VISUAL CONTROL OF ROBOTIC MANIPULATOR BASED ON NEURAL NETWORKS

被引：45

作者：

HASHIMOTO, H

KUBOTA, T

SATO, M

HARASHIMA, F

机构：

[1] Institute of Industrial Science, University of Tokyo, Tokyo

[2] Fujitsu Laboratories Ltd., Kanagawa

[3] Japan Radio Co., Ltd, Tokyo

来源：

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 1992年 / 39卷 / 06期

关键词：

D O I：

10.1109/41.170967

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper describes a control scheme for a robotic manipulator system that uses visual information to position and orientate the end-effector. The control system directly integrates visual data into the servoing process without subdividing the process into determination of the position and orientation of the workpiece and inverse kinematic calculation. The feature of the control scheme is the use of neural networks for the determination of the change in joint angles required in order to achieve the desired position and orientation. The proposed system is able to control the robot so that it can approach the desired position and orientation from arbitrary initial ones. Simulation for the robotic manipulator with six degrees of freedom is done. The validity and the effectiveness of the proposed control scheme are verified by computer simulations.

引用

页码：490 / 496

页数：7

共 12 条

[1] Anderson R.L., Real time intelligent visual control of a robot, Proc. IEEE Int. Workshop Intell. Contr., pp. 89-94, (1985)
[2] Sanderson A.C., Vision and multisensor feedback controllers, Proc. IEEE Int. Workshop Intell. Contr., pp. 80-81, (1985)
[3] Miller W.T., Sensor based control of robotic manipulators using a general learning algorithm, IEEE J. Robotics Automat., RA-3, pp. 157-165, (1987)
[4] Real-time application of neural networks for sensor-based control of robots with vision, IEEE Trans. Syst. Man. Cybem., 19, 4, pp. 825-831, (1989)
[5] Kawato M., Fukukawa K., Suzuki R., A hierarchical-network model for control and learning of voluntary movement, Biol. Cybernet., 57, pp. 169-185, (1987)
[6] Pao Y.H., A connectionist-net approach to autonomous machine learning of effective process control strategies, Proc. Int. Conf. Manufacturing Science Technol. Future, (1987)
[7] Tsai R., Huang T., Uniqueness and estimation of three dimensional motion parameters of rigid objects with curved surfaces, IEEE Trans. Pattern Anal. Machine Intell., PAMI-6, pp. 13-27, (1984)
[8] Feddema J.T., Automatic selection of image features for visual servoing of a robotic manipulator, in, Proc. IEEE Int. Conf. Robotics Automat., pp. 832-837, (1989)
[9] Hung Y., Yeh P., Harwood D., Passive ranging to known planar point sets, Proc. IEEE Int. Conf. Robotics Automat., pp. 80-84, (1985)
[10] Rumelhart D.E., McClelland J.L., Parallel Distributed Processing, vols. 1

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