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24-01-2011, 06:29 PM

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for more on tactile-sensing-system-using-artificial-neural-networks, please go through the following thread.

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24-07-2012, 04:39 PM


.docx   TACTILE SENSING SYSTEM.docx (Size: 78.47 KB / Downloads: 24)


Object Identification plays an important role in various applications ranging from robotics to computer vision. Artificial neural network (ANN) is being used for in various pattern recognition applications due to the advantages of ability as well as adaptability to learn. This paper presents identification of object independent to size, position and orientation using the concept of ANN and moments. The image of the object is taken with the help of the tactile sensing system. This paper describes the complete hardware and software concepts of the system for the object identification with the help of ANN.


Of the many sensing operations performed by the human beings, the one that is probably the most likely to be taken for granted is that of touch. Touch is not only complementary 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.


This system uses conductive elastomer as a sensor, which has property that its conductivity changes as the function of the pressure. Fig 1 shows the configuration of the system. The conductive elastomer is mounted on 8*8 force sensing sites for the measurement of pressure distribution on the object. These force sensing sites are connected through the PC add-on data acquisition card. Stepper motor is used to apply specific amount of pressure for proper identification of the objects. Hardware for scanning the matrix and related signal conditioning is designed along with the stepper motor interface circuitry. Once the image of the object is acquired through the tactile sensing system then it is further processed using image processing concepts for the proper identification and inferring other properties of the objects. Tactile data for the object identification is acquired using row-scanning technique. After the removal of noise from this tactile data it passes to the different modules of the system for further


Main modules of this system are preprocessing, data acquisition, matrix representation graphical representation, edge detection and moments calculations for generating a feature vector. Tactile image acquisition involves conversion of the pressure image into an array of numbers that can be manipulated by the computer. In this system tactile sensor is used to obtain the pressure data of the object and this data is further acquired with the help of data acquisition and data input output card, which are interfaced with the computer. The preprocessing module involves in the removal of the noise, which is essential for acquiring the image of the object under consideration. The image is analyzed by a set of numerical features to remove redundancy from data and reduce its dimensions. Invariant moments are calculated in this module which is required by the next module to the artificial neural for the identification of the object independent to scale, rotation and position.


Main module of this system includes the description of the system and gives many options to the user for processing the tactile data in different forms like automatic or manual processing of the data. Feature extraction module is used for the calculation of the moments from the acquired tactile data. The application of moments provides a method of describing the object in terms of its area, position and the orientation. These invariant moments are used by the ANN as the input neurodes which is the important data for the classification and identification of the object. Flow chart for taking the image identification is shown above in Fig.3.


Stepper motor is used for exerting specific amount of pressure on the object, which is required for the handling of delicate objects, getting proper image of the object and calculating the height of object .First of all stepper motor is arranged in such a way that its angular motion is converted into the linear motion and it was designed in such a way that it travels linear distance of 0.03 mm per step. This part of calibration is also used for calculating the height of the object .To begin with ,motion of the stepper motor was calibrated in terms of pressure applied and the linear displacement . Pressure calibration of stepper motor is done with the help of capacitor pressure sensor in which foam is used as dielectric between two parallel plates of the capacitor .First graph was plotted pressure verses the change in the value of the capacitance .Response of the same is shown in Graph1. Then the same capacitive tactile was used to find the number of steps verses change in capacitance response as shown in Graph 2.


This system is well suited for the classification of the object with the help of ANN and moments. Classification and identification of the object is independent to size, position and orientation of the object under consideration .This system has capability of describing the object under test in different forms like identification , height ,edge, contact area, pressure distribution ,on the object,3-D representation, orientation, position etc of the object. The system has well support of software for processing the tactile data in different forms and taking any decision after the identification of the object. Finally it is observed that this system is intelligent enough for the identification of different types of the object like square, rectangle ,circle, bar, triangle independent to their position ,orientation and scale and giving its many physical properties .This system has various applications in robotics, medical and tele-operations and in computer vision.

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