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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 in Control, Automation and Robotics (ICINCO 06)

Keywords

LAGR, Learning, 4D/RCS, mobile robot, hierarchical control, 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=823008 (Accessed December 9, 2024)

Issues

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

Created June 26, 2006, Updated October 12, 2021