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UGCV PerceptOR Integrated (UPI)
Heads: John Bares and Anthony (Tony) Stentz
Contact: Anthony (Tony) Stentz (tony+@cmu.edu)
Mailing address:
National Robotics Engineering Consortium
10 40th Street
Pittsburgh, PA 15201
Associated center: NREC
For more information, see this project's homepage.
This page last updated - September 2006.
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Project Description |
Personnel |
Sub-projects |
Publications
Project Description
The UPI (UGCV PerceptOR Integrated) program integrates and enhances the results from UGCV and PerceptOR to increase the speed and autonomy of unmanned ground vehicles operating in complex terrain.
By combining the inherent mobility of Spinner and
<../crusher/index.htm>Crusher with advanced perception techniques including the use of learning and prior terrain data, the UPI program stresses system design across vehicle, sensors and software so that the strengths of one component compensate for the weaknesses of another.
Created as a Future Combat Systems (FCS) technology feed program, test results from the UPI program are advancing efforts on many other autonomous vehicle programs, including the Armed Reconnaissance Vehicle and the
<../ans/index.htm>Autonomous Navigation System.
Personnel [Past Members]
Current Sub-projects [Past Sub-projects]
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PerceptOR (NREC) - We have developed a novel semi-autonomous unmanned ground vehicle (UGV) that includes a dedicated unmanned air vehicle - a "Flying Eye" - that flies ahead of the UGV to detect hazards before the onboard UGV sensors would.
Publications
Note: This list may not be comprehensive. It contains only those publications in the RI publications database. Entries are listed in reverse chronological order.
- Toward Optimal Sampling in the Space of Paths
C. Green and A. Kelly
13th International Symposium of Robotics Research, November, 2007.
[Abstract]
Download: pdf [3451 KB], ps.gz [642 KB] copyrighted
- State Space Sampling of Feasible Motions for High Performance Mobile Robot Navigation in Highly Constrained Environments
T. Howard, C. Green, and A. Kelly
Proceedings of the 6th International Conferences on Field and Service Robotics, July, 2007.
[Abstract]
Download: pdf [2007 KB] copyrighted
- Vegetation Detection for Driving in Complex Environments
D. Bradley, R. Unnikrishnan, and J. Bagnell
IEEE International Conference on Robotics and Automation, April, 2007.
[Abstract]
Download: pdf [1694 KB] copyrighted
- Boosting Structured Prediction for Imitation Learning
N. Ratliff, D. Bradley, J. Bagnell, and J. Chestnutt
Advances in Neural Information Processing Systems 19, MIT Press, Cambridge, MA, 2007.
[Abstract]
Download: pdf [847 KB] copyrighted
- Improving Robot Navigation Through Self-Supervised Online Learning
B. Sofman, E.L. Ratliff, J. Bagnell, J. Cole, N. Vandapel, and A. Stentz
Journal of Field Robotics, Vol. 23, No. 12, December, 2006.
[Abstract]
Download: pdf [2114 KB] copyrighted
- Optimal Sampling In the Space of Paths: Preliminary Results
C. Green and A. Kelly
tech. report CMU-RI-TR-06-51, Robotics Institute, Carnegie Mellon University, November, 2006.
[Abstract]
Download: pdf [1713 KB], ps.gz [625 KB] copyrighted
- Experimental Analysis of Overhead Data Processing To Support Long Range Navigation
D. Silver, B. Sofman, N. Vandapel, J. Bagnell, and A. Stentz
IEEE International Conference on Intelligent Robots and Systems (IROS), October, 2006, pp. 2443 - 2450.
[Abstract]
Download: pdf [1196 KB] copyrighted
- Improving Robot Navigation Through Self-Supervised Online Learning
B. Sofman, E.L. Ratliff, J. Bagnell, N. Vandapel, and A. Stentz
Proceedings of Robotics: Science and Systems, August, 2006.
[Abstract]
Download: pdf [1683 KB] copyrighted
- Terrain Classification from Aerial Data to Support Ground Vehicle Navigation
B. Sofman, J. Bagnell, A. Stentz, and N. Vandapel
tech. report CMU-RI-TR-05-39, Robotics Institute, Carnegie Mellon University, January, 2006.
[Abstract]
Download: pdf [697 KB] copyrighted
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