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THE LAGR PROJECT - Integrating Learning Into the 4D/RCS Control Hierarchy

Published

Author(s)

James S. Albus, Roger V. Bostelman, Tsai H. Hong, William P. Shackleford, Michael O. Shneier

Abstract

The National Institute of Standards and Technology s (NIST) Intelligent Systems Division (ISD) has been a part of the Defense Advanced Research Project Agency (DARPA) LAGR (Learning Applied to Ground Robots) Project. The NIST team s objective for the LAGR Project is to insert learning algorithms into the modules that make up the 4D/RCS (Four Dimensional/Real-Time Control System), the standard reference model architecture to which ISD has applied to many intelligent systems. This paper describes the 4D/RCS structure, its application to the LAGR project, and the learning and mobility control algorithms used by the NIST team s vehicle.
Proceedings Title
International Conference on Informatics in Control, Automation and Robotics | 3rd | | Set bal Polytechnic Institute
Conference Dates
August 1-5, 2006
Conference Location
Setubal, 1, PO
Conference Title
International Conference on Informatics in Control, Automation and Robotics

Keywords

4D/RCS, hierarchical control, LAGR, learning, mobile robot, reference model architecture

Citation

Albus, J. , Bostelman, R. , Hong, T. , Shackleford, W. and Shneier, M. (2006), THE LAGR PROJECT - Integrating Learning Into the 4D/RCS Control Hierarchy, International Conference on Informatics in Control, Automation and Robotics | 3rd | | Set bal Polytechnic Institute, Setubal, 1, PO, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=824553 (Accessed July 24, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created August 30, 2006, Updated October 12, 2021