Pattern Recognition of a Grasped Object by Unit-Vector Distribution

A pattern recognition method using an artificial hand to identify the pattern of a grasped object and to locate its position relative to the hand coordinates is discussed. In the proposed recognition method, an object is recognized as a pile of two-dimensional slices, namely, a pile of plane closed curves. Each curve (i.e., contour) is described as the distribution pattern of unit-vectors, called the unit-vector distribution (UVD). The proposed recognition method using UVD functions is as follows. 1) Given the a priori information about the contours of objects to be grasped, the UVD´s of their contours are calculated and memorized. These are called the original patterns (OP´s). 2) Then a sampled UVD is formed from real tactile data and called the data pattern (DP). 3) The DP is compared with the memorized patterns (MP´s), which are obtained by blurring the corresponding OP, so as to make it easier to single out the best fitted OP. 4) Finally, the contour is regenerated in the hand coordinate system by using the UVD of the singled out pattern. An experiment using a trial sensor and a model hand has shown the effectiveness of the proposed method in the recognition of several kinds of objects having cylindrical and prismatic contours.