A study on manufacturing facility safety system using multimedia tools for cyber physical systems

Ko, Dongbeom; Lee, Seunghwa; Park, Jeong-Min

doi:10.1007/s11042-020-09925-z

Cited by 6 publications

(3 citation statements)

References 41 publications

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“…The mechanical components were designed based on the modification of an open-source, six-degree-of-freedom Thor Robot, which was released in 2017 [12]. Since then, the model has undergone many modifications, adaptations, and applications by numerous researchers worldwide and more than 20 units have been built in at least 11 different countries [13][14][15][16][17][18][19]. FreeCAD, an open-source 3D modeling software was used to model the robotic arm.…”

Section: Mechanical Designmentioning

confidence: 99%

UIArm I: Development of a Low-Cost and Modular 4-DOF Robotic Arm for Sorting Plastic Bottles from Waste Stream

Adediran¹,

Ayodeji²,

Kazeem³

et al. 2023

JESA

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The study presents the development of an accessible, reliable, 3D printable, low-cost, and modular 4 degrees-of-freedom robotic arm for the automated sorting of plastic bottles from the waste stream. The UIArm I robot arm was designed based on the modification of an open-source Thor Robot model using Free-CAD with the components 3D printed using PLA and PETG. The forward kinematics was obtained by Denavit-Hartenberg (DH) method, while the analytical method was used for the inverse kinematics. The electrical components include stepper motors, servo motors, motor drivers, a printed circuit board (PCB), an Arduino Mega microprocessor, a light source for illumination, and a PC with a webcam. Python was used for programming the PC and C# for the Arduino microprocessor. TensorFlow, an end-to-end open-source, machine learning platform was used to develop the object detection algorithm based on a deep neural network. The object detection model achieved an accuracy of 91% for Pepsi plastic bottles which formed the bulk of training images. Other types of plastic bottles were detected with an 85% accuracy. The study has demonstrated the viability of a locally developed robotic arm for the automated sorting of plastic bottles.

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Section: Mechanical Designmentioning

confidence: 99%

UIArm I: Development of a Low-Cost and Modular 4-DOF Robotic Arm for Sorting Plastic Bottles from Waste Stream

Adediran¹,

Ayodeji²,

Kazeem³

et al. 2023

JESA

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show abstract

“…Therefore, in order to minimise collisions in these workspaces, used by cobots and human operators, researchers are looking for new solutions related to the prediction of and early warnings against such events. In [4], simulation models devoted to expected collisions, based on the depth-image camera installed outside the equipment, were developed. Next, in [5], a dynamic human-robot fusion algorithm, in order to estimate, in real-time, the minimum human-robot distance requires, based on image processing and 3D representation, is proposed.…”

Section: Introductionmentioning

confidence: 99%

Working toward Solving Safety Issues in Human–Robot Collaboration: A Case Study for Recognising Collisions Using Machine Learning Algorithms

Patalas-Maliszewska,

Dudek,

Pajak

et al. 2024

Electronics

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The monitoring and early avoidance of collisions in a workspace shared by collaborative robots (cobots) and human operators is crucial for assessing the quality of operations and tasks completed within manufacturing. A gap in the research has been observed regarding effective methods to automatically assess the safety of such collaboration, so that employees can work alongside robots, with trust. The main goal of the study is to build a new method for recognising collisions in workspaces shared by the cobot and human operator. For the purposes of the research, a research unit was built with two UR10e cobots and seven series of subsequent of the operator activities, specifically: (1) entering the cobot’s workspace facing forward, (2) turning around in the cobot’s workspace and (3) crouching in the cobot’s workspace, taken as video recordings from three cameras, totalling 484 images, were analysed. This innovative method involves, firstly, isolating the objects using a Convolutional Neutral Network (CNN), namely the Region-Based CNN (YOLOv8 Tiny) for recognising the objects (stage 1). Next, the Non-Maximum Suppression (NMS) algorithm was used for filtering the objects isolated in previous stage, the k-means clustering method and Simple Online Real-Time Tracking (SORT) approach were used for separating and tracking cobots and human operators (stage 2) and the Convolutional Neutral Network (CNN) was used to predict possible collisions (stage 3). The method developed yields 90% accuracy in recognising the object and 96.4% accuracy in predicting collisions accuracy, respectively. The results achieved indicate that understanding human behaviour working with cobots is the new challenge for modern production in the Industry 4.0 and 5.0 concept.

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“…Cameras were used to ensure safety and calculate distances between a person and a robot. Human interactions with an industrial robot were performed using gestures and commands as follows [8]: the camera detects the hand and recognizes the command [9]. The described method improves the level of human-robot interaction without using a remote control.…”

Section: Introductionmentioning

confidence: 99%

Using optical sensors for industrial robot-human interactions in a Gazebo environment.

Kidiraliev,

Lavrenov

2023

Proceedings of International Conference on Artificial Life and Robotics

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This paper presents an overview of a robot operating system based architecture for human-industrial robot interactions using peripheral optical sensors for real-time object detection and collision avoidance with an industrial robot in the virtual world of the Gazebo simulator. Machine vision plays a huge role in production automation, and develop a system based on Kuka KR3 industrial robot for detecting and tracking a human and other objects in a working area using optical sensors. The ability to work in low light and crowded conditions, as well as the ability to reconstruct a method of execution of a task, while maintaining control of a robot. This work considers several optical sensors and a comparative analysis.

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A study on manufacturing facility safety system using multimedia tools for cyber physical systems

Cited by 6 publications

References 41 publications

UIArm I: Development of a Low-Cost and Modular 4-DOF Robotic Arm for Sorting Plastic Bottles from Waste Stream

UIArm I: Development of a Low-Cost and Modular 4-DOF Robotic Arm for Sorting Plastic Bottles from Waste Stream

Working toward Solving Safety Issues in Human–Robot Collaboration: A Case Study for Recognising Collisions Using Machine Learning Algorithms

Using optical sensors for industrial robot-human interactions in a Gazebo environment.

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