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Abstract: An occurrence of diagenetic fluorapatite cement is documented within the Cambro-Ordovician Keeseville Formation, Potsdam Group, near Chateaugay in New York State. The fluorapatite cement occurs as stratiform layers within [...]

Abstract: The Potsdam Group is a Cambrian to Lower Ordovician siliciclastic unit that crops out along the southeastern margins of the Ottawa graben. From its base upward, the Potsdam consists [...]

The Signal Hill Group consists of the youngest Neoproterozoic strata in the Newfoundland Avalon Zone. It records sedimentation coeval with the ca. 560-555 Ma Avalonian orogeny, defined by local deformation [...]

The Signal Hill Group consists of the youngest Neoproterozoic strata in the Newfoundland Avalon Zone. It records sedimentation coeval with the ca. 560-555 Ma Avalonian orogeny, defined by local deformation [...]

This paper describes a vision-based system for 3-D localization of a mobile robot in a natural environment. The system includes a mountable head with three on-board charge-coupled device cameras that can be installed on the robot. The main emphasis of this paper is on the ability to estimate the motion of the robot independently from any prior scene knowledge, landmark, or extra sensory devices. Distinctive scene features are identified using a novel algorithm, and their 3-D locations are estimated with high accuracy by a stereo algorithm. Using new two-stage feature tracking and iterative motion estimation in a symbiotic manner, precise motion vectors are obtained. The 3-D positions of scene features and the robot are refined by a Kalman filtering approach with a complete error-propagation modeling scheme. Experimental results show that good tracking and localization can be achieved using the proposed vision system. Index Terms--Feature-based tracking, robot vision, three-dimensional (3-D) localization, three-dimensional (3-D) trajectory tracking, vision-based tracking, visual motion tracking, visual trajectory tracking.

We have previously developed a mobile robot system which uses scale-invariant visual landmarks to localize and simultaneously build three-dimensional (3-D) maps of unmodified environments. In this paper, we examine global localization, where the robot localizes itself globally, without any prior location estimate. This is achieved by matching distinctive visual landmarks in the current frame to a database map. A Hough transform approach and a RANSAC approach for global localization are compared, showing that RANSAC is much more efficient for matching specific features, but much worse for matching nonspecific features. Moreover, robust global localization can be achieved by matching a small submap of the local region built from multiple frames. This submap alignment algorithm for global localization can be applied to map building, which can be regarded as alignment of multiple 3-D submaps. A global minimization procedure is carried out using the loop closure constraint to avoid the effects of slippage and drift accumulation. Landmark uncertainty is taken into account in the submap alignment and the global minimization process. Experiments show that global localization can be achieved accurately using the scale-invariant landmarks. Our approach of pairwise submap alignment with backward correction in a consistent manner produces a better global 3-D map. Index Terms--Global localization, map building, mobile robots, visual landmarks.

An algorithm is described which rapidly verifies the potential rigidity of three-dimensional point correspondences from a pair of two-dimensional views under perspective projection. The output of the algorithm is a simple yes or no answer to the question "Could these corresponding points from two views be the projection of a rigid configuration?" Potential applications include 3D object recognition from a single previous view and correspondence matching for stereo or motion over widely separated views. The rigidity checking problem is different from the structure-from-motion problem because it is often the case that two views cannot provide an accurate structure-from-motion estimate due to ambiguity and ill conditioning, whereas it is still possible to give an accurate yes/no answer to the rigidity question. Rigidity checking verities point correspondences using 3D recovery equations as a matching condition. The proposed algorithm improves upon other methods that fall under this approach because it works with as few as six corresponding points under full perspective projection, handles correspondences from widely separated views, makes full use of the disparity of the correspondences, and is integrated with a linear algorithm for 3D recovery due to Kontsevich. Results are given for experiments with synthetic and real image data. A complete implementation of this algorithm is being made publicly available. Index Terms - Rigidity checking, point correspondences, image matching, structure-from-motion, nonlinear parameter estimation, perspective projection.

Mass spectrometric techniques use immumoglobin G to map the disulfide linkages and glucosylation sites of the human natriuretic peptide receptor-C (NPR-C) homodimer. The extracellular domain has two intramolecular disulfide bonded loops and three of the four Asn-linked glycosylation centers are occupied. Mutagenesis experiments prove that homodimers form at the juxta membrane site of NPR-C cys residues.