A UGV (unmanned ground vehicle) can better accomplish autonomous mobility through fusion of multiple sensors that provide information concerning the vehicle's location and orientation within the world. Fusion requires an understanding of the constituent elements. This paper describes the application of an egomotion estimator to a sequence of data from a forward-facing video camera on a surrogate UGV, compares the resulting egomotion estimates to those from a co-located inertial navigation system, and defines measures of consistency of the paired observations.
A test course is being implemented at the U.S. Army's Aberdeen Proving Ground (APG), MD, to evaluate the performance of military unmanned ground vehicles (UGV) in traversing off-road terrain. The course is a subset of existing APG automotive test facilities specifically selected to provide challenges to the perception and navigation subsystems as well as to vehicular mobility. Portions of the course currently defined are described in detail, while the overall vision is described in general. Issues addressed in the implementation of this course are discussed, including ground truth and safety. An ideal field test facility is deScribed, and trade-offs in the APG implementation are explained. An actual test using the course to characterize an obstacle detection subsystem is also described. Keywords: Unmanned ground vehicle, vehicle testing, autonomous mobility
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