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Obstacle Detection and Mapping System



H Tsai-Hong, Steven Legowik, M Nashman


This paper discusses and evaluates an obstacle detection algorithm developed at NIST in support of the DEMO III Unmanned Ground Vehicle (UGV) program. The algorithm is a hybrid of grid-based and sensor-based obstacle detection and mapping techniques and is implemented as a module of the integrated 4D-Realtime Control System (RCS) system. The module consists of two sections: An obstacle detection section that processes range data read from a ladar sensor and uses this information to detect obstacles. A mapping section that projects obstacle points onto a grid-based representation map used to generate a traversable path for the vehicle.We describe the sensors used in the 4D-RCS autonomous driving system, the laser range finder (Ladar) sensor's characteristics, the obstacle detection algorithm, and the obstacle mapping procedure. We next evaluate the algorithm's performance on both man-made and natural obstacles. We have demonstrated autonomous driving with obstacle detection and avoidance on the NIST GROUNDS AND THE Nike site at speeds of up to 15 miles per hour.
NIST Interagency/Internal Report (NISTIR) - 6213
Report Number


Vision, Mobility, Unmanned Systems, autonomous driving, image processing, LADAR, negative obstacles, obstacle detection


Tsai-Hong, H. , Legowik, S. and Nashman, M. (1998), Obstacle Detection and Mapping System, NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD, [online], (Accessed April 19, 2024)
Created July 31, 1998, Updated October 12, 2021