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

Published

August 31, 2006

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

Pub Type

Conferences

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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 October 20, 2025)