Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-24T13:53:04.502Z Has data issue: false hasContentIssue false
  • English
  • Français

Conceptual graph-based system for assembly program synthesis

Published online by Cambridge University Press:  09 March 2009

O. Maimon  and
A. Kapitanovsky
O. Maimon
Affiliation:
Tel-Aviv University, Faculty of Engineering Tel-Aviv (Israel)
A. Kapitanovsky
Affiliation:
Tel-Aviv University, Faculty of Engineering Tel-Aviv (Israel)
Get access Rights & Permissions [Opens in a new window]

Summary

ISRA is a support system for robot programming. It provides a means to automatically (guided by knowledge) convert a user's request, expressed in the natural language, into the appropriate conceptual model of the required task. This model incorporates information required for the understanding, planning and sensory-guided performance of the required robotic task.

To develop this system we applied the Natural Computation method. We considered natural information processing by humans during synthesis and interpretation of robotic programs, and then constructed an approximate conceptual model of the relevant dynamically changing real world.

Such a model has to be suitable (e.g. representable and executable) for efficient computer processing. This paper presents the results of a case study which shows that methods built by formalizing human information processing in the robotic domain may be efficiently and naturally implemented in ISRA. It provides evidence that the structure and behavior of ISRA's competence representation and algorithm are comparable with the psychological behavior of humans, as required by the Natural Computation method.

The case study illustrates the use of ISRA for the first phase of an assembly program synthesis i.e. planning of all valid assembly sequences.

Keywords

ISRARobot programmingInformation processing
Type
Article
Information
Robotica , Volume 10 , Issue 4 , July 1992 , pp. 329 - 338
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]Kapitanovsky, A. and Maimon, O., “On automated conversion of natural language requests to robot activities” Technical Report, Tel-Aviv University (1990).Google Scholar
[2]Bonner, S. and Shin, K.G., “A comparative study of robot languages” IEEE Computer 15, No. 12, 82–96 (1983).CrossRefGoogle Scholar
[3]Richards, W.A., “The Approach” In: Natural Computation (Richards, W.A., Ed.) (MIT, Cambridge, Mass., 1988).Google Scholar
[4]Sowa, J.F., Conceptual structures: Information Processing in Mind and Machine (Addison-Wesley Publishing Co., Reading, MA, 1984).Google Scholar
[5]Mac, M. an Airchinnigh, “CAD, KE, and Ada” In: Knowledge Engineering in Computer-Aided Design (Gero, J.S., Ed.) (Elsevier Science Publishers North-Holland, IFIP Amsterdam, 1985) pp. 171–203.Google Scholar
[6]Maimon, O. and Kapitanovsky, A., “From Natural Language Requests to Robot Activities – Towards Bridging the Gap” Proc. of the Sixth Israeli Conf. of Industrial Engineering and Management (1990) pp. 34–38.Google Scholar
[7]De Fasio, T.L. and Whitney, D.E., “Simplified Generation of All Mechanical Assembly Sequences” IEEE J. of Robotics and Automation RA-3, No. 6, 640–658 (1987).Google Scholar
[8]User's Guide of CAEDS Solid Modeling (IBM, 1985).Google Scholar