Robotic tactile recognition of pseudorandom encoded objects

This paper discusses an original model-based method for blind robotic tactile recognition of three-dimensional objects. Conveniently shaped geometric symbols representing terms of a pseudorandom array (PRA) are embossed on object surfaces. Symbols recovered by tactile probing are recognized using a neural network and then clustered in a PRA window that contains enough information to fully identify the absolute coordinates of the recovered window within the encoding PRA. By knowing how different object models were mapped to the PRA, it is possible to unambiguously identify the object face and the exact position of the recovered symbols on the face.

[1]  Dana H. Ballard,et al.  Computer Vision , 1982 .

[2]  Emil M. Petriu,et al.  Two-dimensional position recovery for a free-ranging automated guided vehicle , 1993 .

[3]  Emil M. Petriu,et al.  Active tactile perception of object surface geometric profiles , 1991 .

[4]  Heekuck Oh,et al.  Neural Networks for Pattern Recognition , 1993, Adv. Comput..

[5]  F. MacWilliams,et al.  Pseudo-random sequences and arrays , 1976, Proceedings of the IEEE.

[6]  Peter K. Allen,et al.  Integrating Vision and Touch for Object Recognition Tasks , 1988, Int. J. Robotics Res..

[7]  Niculaie. Trif Model-based visual recognition of 3-D objects using pseudo-random grid encoding. , 1993 .

[8]  R. Spann A two-dimensional correlation property of pseudorandom maximal length sequences , 1965 .

[9]  G. Magenes,et al.  A neural network-based system for tactile exploratory tasks , 1996, Proceedings of International Workshop on Neural Networks for Identification, Control, Robotics and Signal/Image Processing.

[10]  Helen Petrie,et al.  Inexpensive tactile interaction for blind computer users: two application domains , 1997 .

[11]  Susan J. Lederman,et al.  Lessons From the Study of Biological Touch for Robotic Tactile Sensing , 1992 .

[12]  Rangachar Kasturi,et al.  Machine vision , 1995 .

[14]  Kenneth A. Loparo,et al.  Mathematical transforms and correlation techniques for object recognition using tactile data , 1989, IEEE Trans. Robotics Autom..

[15]  Emil M. Petriu,et al.  High sampling resolution tactile sensor for object recognition , 1993, 1993 IEEE Instrumentation and Measurement Technology Conference.

[16]  Costas S. Tzafestas,et al.  Whole-hand kinesthetic feedback and haptic perception in dextrous virtual manipulation , 2003, IEEE Trans. Syst. Man Cybern. Part A.