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Publications (4)0 Total impact

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    ABSTRACT: This paper describes a world model designed to act as a bridge between multiple sensory inputs and a behavior generation (path planning) subsystem for off-road autonomous driving. It describes how the world model map is built and how the objects and features of the world are represented. The functions used to maintain the model are explained and the sensors and sensory processing used to provide data for this application are discussed. The paper includes examples of integrating and fusing sensory data from multiple sources into the world model map. The representation is being developed for the Army's Demo III autonomous driving experiment, which is an on-going research project. The paper concludes with a discussion of future research directions. 1
    03/2001;
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    ABSTRACT: The NIST robot vehicle, a HMMWV with sensors and computer controlled actuators, detects and avoids obstacles while it drives off road at speeds up to 35 km/h. During tests the vehicle drives through the back fields of NIST detecting large obstacles up to 50 m away. Obstacles are sensed using a 30x60 field of view laser range scanner. The planner computes smooth, obstacle free paths that follow an operators commanded path.
    03/2000;
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    Tommy Chang, Steve Legowik, Marilyn N. Abrams
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    ABSTRACT: Obstacle detection and mapping are essential for unmanned autonomous driving. This paper describes both the sensors and the supporting software used in our system for driving autonomously on cross-country roads. The Ladar Range Imaging Camera (EBK) is used for monitoring the environment. We describe an algorithm developed at the National Institute of Standards and Technology (NIST) for detecting obstacles and regions of concealment, and evaluate its ability to detect positive (e.g., rocks) and negative (e.g., ditches) obstacles and concealment regions. We discuss the mapping system used for representing general obstacles (positive, negative, and concealment.) In addition to using information provided by the EBK sensor, the mapping algorithm also uses information supplied by a Global Positioning System (GPS) and an Inertial Navigation System (INS). This system has been tested at NIST and has successfully detected obstacles and regions of concealment while driving cross country at speeds of 35 km/h. 1.
    07/1999;