Self-learning of a robotic arm to pick up wheel bearings using deep neural networks
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...
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2022
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sg-ntu-dr.10356-1584782023-07-07T18:55:51Z Self-learning of a robotic arm to pick up wheel bearings using deep neural networks Mohamed Imran Hussain Mohamed Ishak Soh Yeng Chai School of Electrical and Electronic Engineering EYCSOH@ntu.edu.sg Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics 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. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-06-03T07:01:04Z 2022-06-03T07:01:04Z 2022 Final Year Project (FYP) 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 https://hdl.handle.net/10356/158478 en A3270-211 application/pdf application/octet-stream application/octet-stream Nanyang Technological University |
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Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics Mohamed Imran Hussain Mohamed Ishak Self-learning of a robotic arm to pick up wheel bearings using deep neural networks |
description |
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. |
author2 |
Soh Yeng Chai |
author_facet |
Soh Yeng Chai Mohamed Imran Hussain Mohamed Ishak |
format |
Final Year Project |
author |
Mohamed Imran Hussain Mohamed Ishak |
author_sort |
Mohamed Imran Hussain Mohamed Ishak |
title |
Self-learning of a robotic arm to pick up wheel bearings using deep neural networks |
title_short |
Self-learning of a robotic arm to pick up wheel bearings using deep neural networks |
title_full |
Self-learning of a robotic arm to pick up wheel bearings using deep neural networks |
title_fullStr |
Self-learning of a robotic arm to pick up wheel bearings using deep neural networks |
title_full_unstemmed |
Self-learning of a robotic arm to pick up wheel bearings using deep neural networks |
title_sort |
self-learning of a robotic arm to pick up wheel bearings using deep neural networks |
publisher |
Nanyang Technological University |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/158478 |
_version_ |
1772826296661835776 |