Object tracking robot using adaptive color thresholding

Soans, Rahul Vijay; Ranjith,; Hegde, Abhilash; Singh, Chandra; Kumar, Adithya

doi:10.1109/cesys.2017.8321192

Cited by 10 publications

(1 citation statement)

References 4 publications

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“…Because of the lack of workforces, the enterprise also urgently needs to promote traditional manufacturing plants to a smart manufacturing factory [7][8][9][10][11][12][13][14][15][16][17][18]. The traditional manufacturing plant needs to capture, monitor, and analyze the status and operation data of the facility in real-time to meet the demand of managing production and predictive maintenance [19][20][21][22][23][24].…”

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confidence: 99%

An Intelligent Color Image Recognition and Mobile Control System for Robotic Arm

Yao

Chen

2022

IJRCS

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The aim of this study is to develop intelligent color recognition, mobile control, and monitoring system for a pick-and-place robotic arm for manufacturing systems. The demand for smart manufacturing factories with real-time control of fabricating processes and traceability of production information is increasing urgently. Generally speaking, a smart manufacturing facility is usually composed of sensing, computing, control, and communication technologies together. In this study, the three-tier architecture of the Internet of things (IoT) was adopted as a guideline to design mobile devices to control and monitor a color image recognition and alarm monitoring system by using Raspberry Pi and a web page database. The practical results and contributions of this study are as follows: With integrating the techniques of advanced BR PLC, mobile devices and APP, color image recognition, Raspberry Pi microcomputer, and MySQL database technologies together, (1) the mobile control and monitoring system is able to supervise a real-time manufacturing plant anywhere and anytime with mobile devices easily; (2) the color identification system can identify and classify different color work-piece precisely, and the identification results are recorded for remote database platform; (3) the collected data are analyzed and displayed on mobile devices through the web database for field operators and engineers promptly. It provides a very successful practical paradigm to promote conventional factories to meet industry 4.0.

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