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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)
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 article describes a natural landmark navigation algorithm for autonomous vehicles operating in relatively unstructured environments. The algorithm employs points of maximum curvature, extracted from laser scan data, as point landmarks in an extended Kalman filter. A curvature scale space algorithm is developed to locate points of maximum curvature. The(More)