Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGeraldo, Kent Howarden_US
dc.identifier.citationGeraldo, K. H. (2022). Application of machine learning for autonomous robots in a simplified environment. Final Year Project (FYP), Nanyang Technological University, Singapore.
dc.description.abstractRobomaster 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.en_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Electrical and electronic engineering::Control and instrumentation::Roboticsen_US
dc.titleApplication of machine learning for autonomous robots in a simplified environmenten_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorLap-Pui Chauen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineering (Electrical and Electronic Engineering)en_US
item.fulltextWith Fulltext-
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
Files in This Item:
File Description SizeFormat 
FYP Report.pdf
  Restricted Access
1.71 MBAdobe PDFView/Open

Page view(s)

Updated on Dec 2, 2023


Updated on Dec 2, 2023

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.