Application of machine learning for autonomous robots in a simplified environment
Robomaster University AI Challenge (RMUA) is an annual competition co-hosted by DJI, IEEE, and the International Conference on Robotics and Automation (ICRA). The most recent advancements in AI are implemented and highlighted in this competition. One area that where AI can be used to improve upon...
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2022
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sg-ntu-dr.10356-1580852023-07-07T19:25:55Z Application of machine learning for autonomous robots in a simplified environment Geraldo, Kent Howard Lap-Pui Chau School of Electrical and Electronic Engineering elpchau@ntu.edu.sg Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics Robomaster University AI Challenge (RMUA) is an annual competition co-hosted by DJI, IEEE, and the International Conference on Robotics and Automation (ICRA). The most recent advancements in AI are implemented and highlighted in this competition. One area that where AI can be used to improve upon the existing technology is localization. This paper aims to use machine learning as a method of sensor fusion to localize a robot. Furthermore, in this project, the machine-learning based localization method will be benchmarked and implemented directly with the navigation system. The result shows that the implementation of convolutional neural network as a sensor fusion method shows promise of improving the existing localization methods. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-17T01:38:39Z 2022-05-17T01:38:39Z 2022 Final Year Project (FYP) Geraldo, K. H. (2022). Application of machine learning for autonomous robots in a simplified environment. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158085 https://hdl.handle.net/10356/158085 en application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics Geraldo, Kent Howard Application of machine learning for autonomous robots in a simplified environment |
description |
Robomaster University AI Challenge (RMUA) is an annual competition co-hosted by
DJI, IEEE, and the International Conference on Robotics and Automation (ICRA). The
most recent advancements in AI are implemented and highlighted in this competition.
One area that where AI can be used to improve upon the existing technology is
localization. This paper aims to use machine learning as a method of sensor fusion to
localize a robot. Furthermore, in this project, the machine-learning based localization
method will be benchmarked and implemented directly with the navigation system.
The result shows that the implementation of convolutional neural network as a sensor
fusion method shows promise of improving the existing localization methods. |
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Lap-Pui Chau |
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Lap-Pui Chau Geraldo, Kent Howard |
format |
Final Year Project |
author |
Geraldo, Kent Howard |
author_sort |
Geraldo, Kent Howard |
title |
Application of machine learning for autonomous robots in a simplified environment |
title_short |
Application of machine learning for autonomous robots in a simplified environment |
title_full |
Application of machine learning for autonomous robots in a simplified environment |
title_fullStr |
Application of machine learning for autonomous robots in a simplified environment |
title_full_unstemmed |
Application of machine learning for autonomous robots in a simplified environment |
title_sort |
application of machine learning for autonomous robots in a simplified environment |
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Nanyang Technological University |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/158085 |
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1772826115952345088 |