Automated Visual Inspection: Position Identification of Object for Industrial Robot Application based on Color and Shape

Abstract

Abstract-Inspection task is traditionally carried out by human. However, Automated Visual Inspection (AVI) has gradually become more popular than human inspection due to the advantageous in the aspect of high precision and short processing time. Therefore, this paper proposed a system which identifies the object's position for industrial robot based on colors and shapes where, red, green, blue and circle, square, triangle are recognizable. The proposed system is capable to identify the object's position in three modes, either based on color, shape or both color and shape of the desired objects. During the image processing, RGB color space is utilized by the proposed system while winner take all approach is used to classify the color of the object through the evaluation of the pixel's intensity value of the R, G and B channel. Meanwhile, the shapes and position of the objects are determined based on the compactness and the centroid of the region respectively. Camera settings, such as brightness, contrast and exposure is another important factor which can affect the performance of the proposed system. Lastly, a Graphical User Interface was developed. The experimental result shows that the developed system is highly efficient when implemented in the selected database.

Walking Mobile Robot of Arbitrary Orientation

“…The development of devices for coupling the robot to the displacement surface is the technical solution [13], in which the adhesion mechanism of rock climbing is used. From the point of view of mobile robot navigation and visual inspection of the positions of the robot, interesting works are [14,15], which can be used to program mobile robots. Thus, the task of creating pedipulators, that is, walking mechanisms for mobile robots capable of performing technological operations in a space of arbitrary orientation, is topical.…”

“…Since the rod, which pulls together the rings of the robot's leg, works simultaneously on stretching and bending, the strength condition will have the form: (14) where: S -the area of the rod; 1 W -the moment of resistance; []  -allowable normal voltage. In the case of a rod of the circular cross-section with diameter d 1 , condition (14) takes the form:…”

A Novel Evolutionary Automatic Data Clustering Algorithm using Teaching-Learning-Based Optimization

“…EA are able to provide a solution by approximation within adequately short time and have the ability to avoid getting stuck in local optima [2]. These algorithms searches input parameter values called solutions and results most favorable output parameter values [28].…”