Rinat Ibrayev

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This paper studies the recognition of low-degree polynomial curves based on minimal tac-tile data. Euclidean differential and semi-differential invariants have been derived for quadratic curves and special cubic curves that are found in applications. These invariants, independent of translation and rotation, are evaluated over the differential geometry at(More)
Model-based recognition of an object typically involves matching dense 3D range data. The computational cost is directly affected by the amount of data of which a transformation needs to be found before carrying out the match against a model. This paper investigates recognition using "one-dimensional" data, more specifically, points sampled along three(More)
This paper studies the recognition and localization of 2-D shapes bounded by low-degree polynomial curve segments based on minimal tactile data. We have derived differential invariants for quadratic curves and two special classes of cubic curves. Such an invariant, independent of translation and rotation, is computed from the local geometry at any two(More)
This paper presents a method for recognition of 3D objects with curved surfaces from linear tactile data. For every surface model in a given database, a lookup table is constructed to store principal curvatures precomputed at points of discretization on the surface. To recognize an object, a robot hand with touch sensing capability obtains data points on(More)
In this paper we study the recognition of low-degree polynomial curves based on minimal tactile data. Euclidean differential and semidifferential invariants have been derived for quadratic curves and special cubic curves that are found in applications. These invari-ants, independent of translation and rotation, are evaluated over the differential geometry(More)
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