Automatic Recognition of Low Resolution Tactile Sensing Data Using Rapid Transformation
A pattern is the description of an object that is sensed by appropriate hardware to form a useful data set, which in turn can be processed by a computer. In this paper, we concentrate on a class of patterns arising from geometrical figure approximations as encountered in robotics applications. A wide assortment of devices and systems exists today for data sensing of the environment in the robotics world. Generally speaking, we can classify them into two major classes: non-contact sensing and contact sensing. Non-contact sensing includes optical, sonic, ultrasonic, and magnetic ranging. Contact sensing is the area of tactile sensing with which this research is primarily concerned. A suitable definition of tactile sensing is expressed as continuously variable touch sensing over an array with a certain spatial resolution.
Unable to display preview. Download preview PDF.
List of References
- H. Andrews, W. Pratt, and K. Caspari, Computer Techniques in Image Processing Academic Press, Inc. New York, (1970)Google Scholar
- K.S. Fu, ‘Recent Developments in Pattern Recognition,’ IEEE Trans, on Computers, Vol. C-29, NO. 10 pp. 846, (October, 1980).Google Scholar
- M.D. Wagh and S.C. Kanetkar, ‘A Class of Translation Invariant Transforms, IEEE Trans, on Acoustics, Speech, and Signal Processing pp. 203–205, April 1977.Google Scholar
- Xaver Muller, Holger Schutte, and Hans Burkhardt, ‘Two Dimensional, Fast Transforms with High Degree of Completeness for Translation Invariant Pattern Recognition Problem,’ IEEE Pattern Recognition pp. 170–173, (1980).Google Scholar
- Kai-Kuang Ma ‘Automatic Recognition of Low Resolution Tactile Sensing Data Using Rapid Transformation’ Technical Report Robotics — EE — 82–02, Department of Electrical Engineering, Duke University.Google Scholar