| Author(s): |
James S. Albus; Roger V. Bostelman; Tsai Hong Hong; William P. Shackleford; Michael O. Shneier; |
| Title: |
THE LAGR PROJECT - Integrating learning into the 4D/RCS Control Hierarchy |
| Published: |
June 27, 2006 |
| 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. |
| Conference: |
International Conference in Control, Automation and Robotics (ICINCO 06) |
| Proceedings: |
International Conference on Informatics in Control, Automation and Robotics | 3rd | | Set bal Polytechnic Institute |
| Location: |
Setubal, PO |
| Dates: |
August 1-5, 2006 |
| Keywords: |
LAGR, Learning, 4D/RCS, mobile robot, hierarchical control, reference model architecture |
| Research Areas: |
Systems Integration |
| PDF version: |
 Click here to retrieve PDF version of paper (723KB) |
