Please use this identifier to cite or link to this item: http://dspace.aiub.edu:8080/jspui/handle/123456789/2887
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dc.contributor.authorMondal, Shuvra-
dc.contributor.authorSharon, Nadif Farhin-
dc.contributor.authorTabassum, Kaniz Mohosina-
dc.contributor.authorMuna, Umme Habiba-
dc.contributor.authorAlam, Nowshin-
dc.date.accessioned2025-09-29T03:37:10Z-
dc.date.available2025-09-29T03:37:10Z-
dc.date.issued2024-02-27-
dc.identifier.citationhttps://doi.org/10.1109/ICCIT60459.2023.10441038en_US
dc.identifier.isbnElectronic ISBN:979-8-3503-5901-5-
dc.identifier.urihttp://dspace.aiub.edu:8080/jspui/handle/123456789/2887-
dc.description.abstractAs the era of fourth industrial revolution approaches automation via robotic arms in the industrial and daily work routine are getting more attention. Robotic assistance can play a major role in efficient production and assembly lines by eliminating human error and producing more precise tasks. Moreover, such robots can help to reduce the accident risk for humans in hazardous conditions. In this research a low-cost, feasible, and easy to build robot arm has been presented which can distinguish colors and can pick and place light objects autonomously. The gripper and two wheeled robots were controlled by an Arduino UNO microcontroller to move and pick and place function with four degrees of freedom. A pixy2 camera sensor was used for object color detection which works independently with an internal microprocessor that uses a color-filtering algorithm based on hue. The fully automated prototype robot utilizes real-time image processing and path learning to successfully detect objects with six different colors and do pick and place operation within its pre-trained path or task. The prototype robot showed over 75% accuracy and an average of 15 seconds of operation time while picking and placing different colored objects autonomously.en_US
dc.language.isoen_USen_US
dc.publisherIEEE Exploreen_US
dc.relation.ispartofseries2023 26th International Conference on Computer and Information Technology (ICCIT);-
dc.subjectRobotic Arm , Color Detection , Degrees Of Freedom , Image Processing , Production Line , Image Sensor , Assembly Line , Fourth Industrial Revolution , Object Color , Hazardous Conditions , Arduino UNO , Deep Learning , Convolutional Neural Network , Red Color , 3D Printing , Precise Control , Green Color , Object Detection , Orange Color , Buck Converter , Servo Motor , Self-driving , Visual Servoing , Robotic System , Iterative Closest Point , Visual Control , Electrical Engineering , Neural Network Controlen_US
dc.titleDevelopment of a Low-Cost Real Time Color Detection Capable Robotic Armen_US
dc.typeArticleen_US
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