Grasp Exploration for 3D Object Shape Representation Using Probabilistic Map
Résumé
In this work it is shown the representation of 3D
object shape acquired from grasp exploration. Electromagnetic motion
tracking sensors are used on the fingers for object contour following to
acquire the 3D points to represent its shape using a probabilistic
volumetric map. It is used the object referential for its
representation. For that, it is found the center of mass of the 3D
object through the moments to define its referential. The occupancy of
each individual voxel in the map is assumed to be independent from the
other voxels occupancy. The posteriori achieved from Bayes' rule is the
probability distribution on the occupations percentage for each voxel.
The probabilistic map in a Cartesian system is converted to the
spherical coordinate system for visualization with more details on its
surface.
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