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The International Journal of Robotics Research
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Shape Description of Curved Surfaces from Contact Sensing Using Surface Normals

M. Charlebois

K. Gupta

S. Payandeh

Robotics Laboratory, School of Engineering Science, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada

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.

The International Journal of Robotics Research, Vol. 18, No. 8, 779-787 (1999)
DOI: 10.1177/02783649922066556
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Shandong Wu and Y.F. Li
On Signature Invariants for Effective Motion Trajectory Recognition
The International Journal of Robotics Research, August 1, 2008; 27(8): 895 - 917.
[Abstract] [PDF]