The LAGR Project. Integrating learning into the 4D/RCS Control Hierarchy

Published

August 1, 2006

Author(s)

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

Abstract

The National Institute of Standards and Technology?s (NIST) Intelligent Systems Division (ISD) is a par-ticipant in 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 methods used by the NIST team?s vehicle.

Proceedings Title

Proceedings of ICINCO 06 International Conference in Control

Conference Dates

August 1, 2006

Conference Location

Setubal, Portugal, 1, USA

Conference Title

International Conference in Control Automation and Robotics

Pub Type

Conferences

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Keywords

4D/RCS, Control, hierarchical control, LAGR, learning, mobile robot, Mobility, Robotics & Intelligent Systems, Unmanned Systems

Citation

Albus, J. , Bostelman, R. , Hong, T. , Chang, T. , Shackleford, W. and Shneier, M. (2006), The LAGR Project. Integrating learning into the 4D/RCS Control Hierarchy, Proceedings of ICINCO 06 International Conference in Control, Setubal, Portugal, 1, USA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822701 (Accessed December 7, 2024)