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Boss is an autonomous vehicle that uses on-board sensors (global positioning system, lasers, radars, and cameras) to track other vehicles, detect static obstacles, and localize itself relative to a road model. A three-layer planning system combines mission, behav-ioral, and motion planning to drive in urban environments. The mission planning layer considers(More)
—This paper describes the obstacle detection and tracking algorithms developed for Boss, which is Carnegie Mellon University 's winning entry in the 2007 DARPA Urban Challenge. We describe the tracking subsystem and show how it functions in the context of the larger perception system. The tracking subsystem gives the robot the ability to understand complex(More)
(DARPA) announced the first Grand Challenge with the goal of developing vehicles capable of autonomously navigating desert trails and roads at high speeds. The competition was generated as a response to a mandate from the United States Congress that a third of U.S. military ground vehicles be unmanned by 2015. To achieve this goal DARPA drew from(More)
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