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Novel Robotic Arm Working-Area AI Protection System

Jeng-Dao Lee, En-Shuo Jheng, Chia-Chen Kuo, Hongming Chen, Ying-Hsiu Hung

Year
2023
Citations
3
Access
Open access

Abstract

From traditionally handmade items to the ability of people to use machines to process and even to human-robot collaboration, there are many risks. Traditional manual lathes and milling machines, sophisticated robotic arms, and computer numerical control (CNC) operations are quite dangerous. To ensure the safety of workers in automated factories, a novel and efficient warning-range algorithm is proposed to determine whether a person is in the warning range, introducing YOLOv4 tiny-object detection algorithms to improve the accuracy of determining objects. The results are displayed on a stack light and sent through an M-JPEG streaming server so that the detected image can be displayed through the browser. According to the experimental results of this system installed on a robotic arm workstation, it is proved that it can ensure recognition reaches 97%. When a person enters the dangerous range of the working robotic arm, the arm can be stopped within about 50 ms, which will effectively improve the safety of its use.

Keywords

Robotic armWorkstationProcess (computing)Computer scienceRange (aeronautics)AutomationRobotArtificial intelligenceSimulationEmbedded system

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