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

James Albus, Roger Bostelman, Tsai Hong, Tommy Chang, Will Shackleford, Michael Shneier

Abstract

The National Institute of Standards and Technology’s (NIST) Intelligent Systems Division (ISD) is a participant 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.

References

  1. Albus, J.S., Juberts, M., Szabo, S., RCS: A Reference Model Architecture for Intelligent Vehicle and Highway Systems, Proceedings of the 25th Silver Jubilee International Symposium on Automotive Technology and Automation, Florence, Italy, June 1-5, 1992.
  2. Albus, J.S., Huang, H.M., Messina, E., Murphy, K.N., Juberts, M., Lacaze, A., Balakirsky, S.B., Shneier, M.O., Hong, T.H., Scott, H.A., Proctor, F.M., Shackleford, W., Michaloski, J.L., Wavering, A.J., Kramer, Tom , Dagalakis, N.G., Rippey, W.G., Stouffer, K.A., 4D/RCS Version 2.0: A Reference Model Architecture for Unmanned Vehicle Systems, NISTIR, 2002.
  3. Albus, J.S., Balakirsky, S.B., Messina, E., Architecting A Simulation and Development Environment for MultiRobot Teams, Proceedings of the International Workshop on Multi Robot Systems, Washington, DC, March 18 - 20, 2002
  4. Balakirsky, S.B., Chang, T., Hong, T.H., Messina, E., Shneier, M.O., A Hierarchical World Model for an Autonomous Scout Vehicle, Proceedings of the SPIE 16th Annual International Symposium on Aerospace/Defense Sensing, Simulation, and Controls, Orlando, FL, April 1-5, 2002.
  5. Bostelman, R.V., Jacoff, A., Dagalakis, N.G., Albus, J.S., RCS-Based RoboCrane Integration, Proceedings of the International Conference on Intelligent Systems: A Semiotic Perspective, Gaithersburg, MD, October 20- 23, 1996.
  6. Chang, T., Hong, T., Legowik, S., Abrams, M., Concealment and Obstacle Detection for Autonomous Driving, Proceedings of the Robotics & Applications Conference, Santa Barbara, CA, October, 1999.
  7. Heyes-Jones, J., A* algorithm tutorial, 2005 http://us.geocities.com/jheyesjones/astar.html.
  8. Shneier, M., Chang, T., Hong, T., and Shackleford, W., Learning Traversability Models for Autonomous Mobile Vehicles, Autonomous Robots (submitted), 2006.
  9. Jackel, Larry, LAGR Mission, http://www.darpa.mil/ipto/programs/lagr/index.htm, DARPA Information Processing Technology Office, 2005
  10. Konolige, K., SRI Stereo Engine, 2005 http://www.ai.sri.com/konolige/svs/.
  11. Michaloski, J.L., Warsaw, B.A., Robot Control System Based on Forth, Robotics Engineering, Vol. 8, No. 5, pgs 22-26, May, 1896.
  12. Ojala, T., Pietikäinen, M., and Harwood, D., A Comparative Study of Texture Measures with Classification Based on Feature Distributions, Pattern Recognition, 29: 51-59, 1996.
  13. Oskard, D., Hong, T., Shaffer, C., Real-time Algorithms and Data Structures for Underwater Mapping, National Institute of Standards and Technology, 1990.
  14. Shackleford, W., The NML Programmer's Guide (C++ Version), 1990.
  15. Shackleford, W., Stouffer, K.A., Implementation of VRML/Java Web-based Animation and Communications for the Next Generation Inspection System (NGIS) Real-time Controller, Proceedings of the ASME International 20th Computers and Information in Engineering (CIE) Conference, Baltimore, MD, September 10 - 13, 2000.
  16. Tan, C., Hong, T., Shneier, M., and Chang, T., "Color Model-Based Real-Time Learning for Road Following," in Proc. of the IEEE Intelligent Transportation Systems Conference (Submitted) Toronto, Canada, 2006
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Paper Citation


in Harvard Style

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 . In Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-972-8865-60-3, pages 154-161. DOI: 10.5220/0001210701540161


in Bibtex Style

@conference{icinco06,
author={James Albus and Roger Bostelman and Tsai Hong and Tommy Chang and Will Shackleford and Michael Shneier},
title={THE LAGR PROJECT - Integrating Learning into the 4D/RCS Control Hierarchy},
booktitle={Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2006},
pages={154-161},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001210701540161},
isbn={978-972-8865-60-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - THE LAGR PROJECT - Integrating Learning into the 4D/RCS Control Hierarchy
SN - 978-972-8865-60-3
AU - Albus J.
AU - Bostelman R.
AU - Hong T.
AU - Chang T.
AU - Shackleford W.
AU - Shneier M.
PY - 2006
SP - 154
EP - 161
DO - 10.5220/0001210701540161