Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/158478
Title: Self-learning of a robotic arm to pick up wheel bearings using deep neural networks
Authors: Mohamed Imran Hussain Mohamed Ishak
Keywords: Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Mohamed Imran Hussain Mohamed Ishak (2022). Self-learning of a robotic arm to pick up wheel bearings using deep neural networks. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158478
Project: A3270-211
Abstract: The field of robotics has been becoming increasingly popular over the years because of their various benefits and prospects. Incorporating them into a factory setting can bring about faster production times, reduced waste of materials and resources, and better utilization of manpower. This project aims to simulate a factory setting with mobile robots working in it while avoiding obstacles when navigating the factory. The original project, “Self-learning of a robotic arm to pick up wheel bearings using deep neural networks”, allocated to me was terminated and the current project was undertaken due to a change of supervisor in semester one of the academic year. As a result, I had approximately only one semester to complete the project. The project title is still the old project’s title however because the deadline to change it was over.
URI: https://hdl.handle.net/10356/158478
Schools: School of Electrical and Electronic Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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U1923351H - FYP Final Report - (A3270-211).pdf
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10.15 MBAdobe PDFView/Open
Simulation.mp4
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10.88 MBUnknownView/Open
Communication.mp4
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3.03 MBUnknownView/Open

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