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—An Extended Kalman Filter-based algorithm for the localization of a team of robots is described in this paper. The distributed EKF localization scheme is straightforward in that the individual robots maintain a pose estimate using EKFs that are local to every robot. We then show how these results can be extended to perform heterogeneous cooperative(More)
PRIDE (PRediction In Dynamic Environments) is a framework that provides an autonomous vehicle's planning system with information that it needs to perform path planning in the presence of moving objects. The underlying concept is based upon a multi-resolutional, hierarchical approach that incorporates multiple prediction algorithms into a single, unifying(More)
The subject of this article is a scheme for distributed outdoor localization of a team of robots and the use of the robot team for outdoor terrain mapping. Localization is accomplished via Extended Kalman Filtering (EKF). In the distributed EKF-based scheme for localization, heterogeneity of the available sensors is exploited in the absence or degradation(More)
— This paper describes a terrain-aided navigation system that employs points of maximum curvature extracted from laser scan data as primary landmarks. A scale space method is used to extract points of maximum curvature from laser range scans of unmodified outdoor environments. This information is then fused with odometric information to provide localization(More)
— This paper describes the development of a terrain-aided localization framework for autonomous land vehicles operating at high speeds in unstructured, expansive and harsh environments. The localization framework developed is sufficiently generic to be used on a variety of other autonomous land vehicles and is demonstrated by its implementation using field(More)