Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-25T02:54:37.604Z Has data issue: false hasContentIssue false
  • English
  • Français

Learning Task Strategies in Robotic Assembly Systems

Published online by Cambridge University Press:  09 March 2009

D. S. Ahn ,
H. S. Cho ,
K. Ide ,
F. Miyazaki  and
S. Arimoto
D. S. Ahn
Affiliation:
Korea Advanced Institute of Science & Technology, P.O. Box 150, Chongryangri, Seoul (Korea)
H. S. Cho
Affiliation:
Korea Advanced Institute of Science & Technology, P.O. Box 150, Chongryangri, Seoul (Korea)
K. Ide
Affiliation:
Faculty of Engineering Science, Osaka University, Osaka (Japan)
F. Miyazaki
Affiliation:
Faculty of Engineering Science, Osaka University, Osaka (Japan)
S. Arimoto
Affiliation:
Faculty of Engineering, University of Tokyo, Tokyo (Japan)
Get access Rights & Permissions [Opens in a new window]

Summary

This paper presents a practical method for generating task strategies applicable to chamferless and high-precision assembly. The difficulties in devising reliable assembly strategies result from various forms of uncertainty such as imperfect knowledge on the parts being assembled and functional limitations of the assembly devices.

In order to cope with these problems, the robot is provided with the capability of learning the corrective motion in response to the force signal through iterative task execution. The strategy is realized by adopting a learning algorithm and is represented in a binary tree-type database. To verify the effectiveness of the proposed algorithm, a series of experiments are carried out under simulated real production conditions. The experimental results show that sensory signal-to-robot action mapping can be acquired effectively and, consequently, the assembly task can be performed successfully.

Keywords

Chamferless assemblyTask strategyLearningMapping relation
Type
Article
Information
Robotica , Volume 10 , Issue 5 , September 1992 , pp. 409 - 418
Copyright
Copyright © Cambridge University Press 1992

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Nevins, J.L. and Whitney, D.E., “Assembly Research”, Automatica 16, 595–613 (1980).CrossRefGoogle Scholar
2.Whitney, D.E., “Quasi-Static Assembly of Compliantly Supported Rigid Parts” Trans. ASME J. Dyn. Sys. Meas, and Con. 104, 65–77 (1982).CrossRefGoogle Scholar
3.Jeong, K.W. and Cho, H.S., “Development of a pneumatic vibratory wrist for robotic assembly” Robotica 7, part 1, 9–16 (1989).CrossRefGoogle Scholar
4.Cho, H.S., Warnecke, H.T. and Kweon, D.G., “Robotic Assembly: a synthesizing overview” Robotica 5, part 2, 153–165 (1987).CrossRefGoogle Scholar
5.Asada, H. and Hirai, S., “Towards a Symbolic-Level Force Feedback Recognition of Assembly Process States” Proc. 5-th Int. Symp. of Robotics Research, Tokyo (1989) pp. 341–346.Google Scholar
6.Asada, H., “Teaching and Learning of Compliance Using Neural Nets” Proc. IEEE. Int. Conf. Robotics 7, 9–16 (1990).Google Scholar
7.Caine, M.E. et al. , “Assembly Strategies for Chamferless Parts” Proc. IEEE Int. Conf. Robotics and Automation 472–477 (1989).Google Scholar
8.Goto, T., Takeyasu, K. and Inoyama, T., “Control Algorithm for Precise Insert Operation Robots” IEEE Trans, on Sys. Man. and Cyber, SMC-10, No. 1, 19–25 (1980).Google Scholar
9.Vaaler, E. and Seering, W., “Automated Assembly with Systems Having Significant Manipulator and Part Location Errors” Proc. IEEE Int Conf. Robotics and Automation 1357–1360 (1987).Google Scholar
10.Simons, J., Van Brussel, H., De Schutter, I. and Verhaert, J., “A Self-Learning Automation with Variable Resolution for High Precision Assembly by Industrial Robots” IEEE Trans, on Automatic Control AC-27, No. 5, 1109–1113 (1982).Google Scholar
11.Suzuki, H., “Study of Universal Learning Machine Based on a Self-organization Algorithm” Ph. D Thesis, Osaka University 15–25 (1988).Google Scholar
12.Pai, D.K. and Leu, M.C., “The Effect of a Robot Manipulators Uncertainty and Compliance on Task Feasibility” Japan-USA Symp. on Flexible Automation, 979–984 (1990).Google Scholar
13.Gottschlich, S.N. and Kak, A.C., “A Dynamic Approach to High-precision Parts Mating” IEEE Int. Conf. on Robotics and Automation 1246–1253 (1988).Google Scholar