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Performance Analysis of Unmanned Vehicle Positioning and Obstacle Mapping



Roger V. Bostelman, Tsai Hong Hong, Rajmohan Madhavan, Tommy Chang, Harry A. Scott


As unmanned ground vehicles take on more and more intelligent tasks, determination of potential obstacles and accurate estimation of their position become critical for successful navigation and path planning. The performance analysis of obstacle mapping and unmanned vehicle positioning in outdoor environments is the subject of this paper. Recently, the National Institute of Standards and Technology?s (NIST) Intelligent Systems Division has been a part of the Defense Advanced Research Project Agency LAGR (Learning Applied to Ground Robots) Program. NIST's objective for the LAGR Project is to insert learning algorithms into the modules that make up the NIST 4D/RCS (Four Dimensional/Real-Time Control System) standard reference model architecture which has been successfully applied to many intelligent systems. We detail world modeling techniques used in the 4D/RCS architecture and then analyze the high precision maps generated by the vehicle world modeling algorithms as compared to ground truth obtained from an independent differential GPS system operable throughout most of the NIST campus. This work has implications, not only for outdoor vehicles but also, for indoor automated guided vehicles where future systems will have more and more onboard intelligence requiring non-contact sensors to provide accurate vehicle and object positioning.
Conference Dates
April 17-21, 2006
Conference Location
Orlando, FL
Conference Title
SPIE 06-International Society for Optical Engineering, Defense and Security Symposium


Control, global positioning system, ground truth, mapping, Mobility, performance analysis, Performance Metrics, Robotics & Intelligent Systems, stereo vision


Bostelman, R. , , T. , Madhavan, R. , Chang, T. and Scott, H. (2006), Performance Analysis of Unmanned Vehicle Positioning and Obstacle Mapping, SPIE 06-International Society for Optical Engineering, Defense and Security Symposium, Orlando, FL, [online], (Accessed June 17, 2024)


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Created June 27, 2006, Updated February 19, 2017