Shape description of curved surfaces from contact sensing using surface normals

We describe a spline-based framework for incorporating both position and surface-normal information into estimates of curvature based 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 surface-normal 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-the-shelf force/moment sensor to obtain the position and surface-normal data show that despite coarse resolution of the sensor this approach succeeds in qualitative shape recognition.