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Abstract

We describe a spline-based framework for incorporating both position and surface-normal information into estimates of curvaturebased shape parameters. Such position and normal data can be obtained with different types of contact sensors, for example, tactile sensors, force-moment sensors, etc. The heart of our framework is an extended B-spline formulation that incorporates the surfacenormal information into a B-spline surface fit of the position data. The surface-normal information provides additional constraints for the surface fit, and can also significantly improve the approximation of the surface. Curvature-based shape parameters applied to this B-spline surface are then used to characterize the local shape of the object surface. Preliminary experiments with simple primitives—spherical, cylindrical, and planar shapes—and an off theshelf force/moment sensor to obtain the position and surfacenormal data show that despite coarse resolution of the sensor, this approach succeeds in qualitative shape recognition.

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Shape Description of Curved Surfaces from Contact Sensing Using Surface Normals

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