Intelligent vision-based navigation system for mobile robot: A technological review

Vision system is gradually becoming more important. As computing technology advances, it has been widely utilized in many industrial and service sectors. One of the critical applications for vision system is to navigate mobile robot safely. In order to do so, several technological elements are required. This article focuses on reviewing recent researches conducted on the intelligent vision-based navigation system for the mobile robot. These include the utilization of mobile robot in various sectors such as manufacturing, warehouse, agriculture, outdoor navigation and other service sectors. Multiple intelligent algorithms used in developing robot vision system were also reviewed

Simulation-Based Multi-Objective Optimization For Distributed Material Transportation System

Material Transportation System (MTS) is required to move materials within a factory, warehouse, or other facilities. This study focused on AGV where the optimization of MTS is further studied. Although there is increasing demand in AGV control architecture, there is still unexplored potential in optimizing AGV performance measures. Applying AGVs in logistic factory may help in improving the efficiency in material flow and distribution among workstation at the right time and the right place. The aim of this study is to propose a simulation-based vehicle requirement analysis of AGVs in warehouse area with low mixed product variation. Simulations results show optimized number of AGV in warehouse area is achieved and succeed in produce short cycle time with high throughput

Classification of weld bead defects based on image segmentation method

Defect is an imperfection that could impair the worth and utility of a finished good. The defects show some disorder of the product and it is opposite the standard or criteria that have been stated. In defining and detecting the defects occur, many ways have been discussed and observed. However, the techniques or ways are not appropriate or not suitable for some condition and situation. In addition, welding process is one of the critical processes in detecting and defining defect to ensure the quality of the weld bead. To overcome the problem in detecting and defining defects, image processing is one of the methods in improving the process of detecting defects. The defects are classified based on automatic thresholding method that automates detecting and defining the defects. This study proposes a Decision Tree-based classification of weld bead defects through segmentation of image. The result obtained shows that the classification is effective in identifying the weld bead defects with 89% accuracy. For future work, the focus will be made to improve the detection accuracy by integrating suitable filters