Edge detection plays an important role in object recognition and exploration. In this paper, we propose an efficient tracking algorithm, which uses a coarse resolution tactile sensor set, for edge detection of a 2D shape object. Although many researchers have often used a tactile sensor with high resolution such as a 10x10 or higher for edge detection, in this research, we use a 2x2 tactile sensor to track the edges of an object. Using this type of low resolution sensor, we can reduce the manufacturing cost of the sensor and simplify the calculation and control process. In our algorithm, we only need to control the sensor to make it move along the vertical axis, Oy, or the horizontal axis, Ox. The sensor is moved along a suitable direction according to the sensing signals receiving from it. A set of simulations for both convex and concave shapes has been done to verify the algorithm. In addition, methods to increase the accuracy of the algorithm are also discussed.

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Edge detection is always an interesting field for researchers in the area of artificial intelligence, including machine visions and robotics. In the context of tactile sensors, many studies have been conducted on edgeidentification algorithms. These investigations often use high-resolution tactile sensor arrays to track an edge of a large object. In this work, edge identification is examined in which a coarse-resolution tactile sensor, specif., a 2x2 array, is used to detect and track edges of a small object. To simplify the control, we control the sensor just in 2D and in just one direction at a time. We propose two methods to solve this problem: a scanning method, of which the principle of operation is similar to that of a scanner, and an edge-following method that can make the sensor follow the boundary of the object. The flowchart of each method will be presented in detail in this paper. Some simulations in MATLAB, including four shapes, viz., square, triangle, ellipse, and hexagon, have been executed to verify our proposal. A comparison and a critique of the two methods are also presented for improving the methods.

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