TACTILE SENSING SYSTEM USING ARTIFICIAL NEURAL NETWORK

Of the many sensing operations performed by human beings, the one that is probably the most likely to be taken for granted is that of touch. Touch is not only complimentary to vision, but it offers many powerful sensing capabilities. Tactile sensing is another name of touch sensing, which deals with the acquisition of information about the object simply by touching that object. Touch sensing gives the information about the object like shape, hardness, surface details and height of the object, etc.
Tactile sensing is required when an intelligent robot wants to perform delicate assembly operations. During this assembly operation an industrial robot must be capable of recognizing parts, determining their position, orientation and sensing any problem encountered during the assembly from the interface of the parts. Keeping all these things in mind, a Tactile Sensing System is developed which uses image processing techniques for pre-processing and analysis along with ANN’s for object identification. Classification of the object independent of translation, scale and rotation is a difficult task. The concept of Artificial Neural Network is used in this system for the proper identification of the object, irrespective of their size, position and orientation.

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