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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, 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

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 February 27, 2024)
Created July 31, 2006, Updated October 12, 2021