Hostname: page-component-77c89778f8-gq7q9 Total loading time: 0 Render date: 2024-07-17T07:27:40.312Z Has data issue: false hasContentIssue false
  • English
  • Français

Servoed world models as interfaces between robot control systems and sensory data*

Published online by Cambridge University Press:  09 March 2009

Ernest W. Kent  and
James S. Albus
Ernest W. Kent
Affiliation:
National Bureau of Standards, Washington, D.C. 20234 (U.S.A.)
James S. Albus
Affiliation:
National Bureau of Standards, Washington, D.C. 20234 (U.S.A.)
Get access Rights & Permissions [Opens in a new window]

Summary

A hierarchical robot sensory system being developed for industrial robotics is described. At each level of the hierarchy, sensory interpretative processes are guided by expectancy-generating modeling processes. The modeling processes are driven by a priori knowledge (object prototypes), by knowledge of the robot's movements (feed-forward from the control system), and by feedback from the interpretative processes (prior state of the sensory world). At the lowest level, the senses (vision, proximity, tactile, force, joint angle, etc.) are handled separately; above this level, they are integrated into a multi-model world model. At successively higher levels, the interpretative and modeling processes describe the world with successively higher order constructs, and over successively longer time periods. Each level of the modeling hierarchy provides output, in parallel, to guide the corresponding levels of a hierarchical robot control system.

Type
Article
Information
Robotica , Volume 2 , Issue 1 , January 1984 , pp. 17 - 25
Copyright
Copyright © Cambridge University Press 1984

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.Albus, J.S., Barbera, A.J. and Nagel, R.N., Theory and Practice of Hierarchical Control. In: 23rd IEEE Computer Soc. International Conference (09, 1981) pp. 18–39.Google Scholar
2.Koenderink, J.J. and van Doom, A.J., The Internal Rep-resentation of Solid Shape with Respect to Vision. Biol. Cybernetics 32, 211–216 (1979).CrossRefGoogle Scholar
3.Albus, J.S., Kent, E.W., Nashman, M., Mansbach, P., Palombo, L. and Shneier, M., A 6-D Vision System. Proc. SPIE Technical Symposium, Crystal City, VA. (05 1982).Google Scholar