Mobile robot navigation using deep learning
The ability to navigate is a key aspect of mobile robots, especially so for autonomous ones. However, the presence of glare has always been an issue for them. As these autonomous mobile robots do not have human supervision, they navigate primarily through the use of their onboard cameras for environ...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2020
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| Online Access: | https://hdl.handle.net/10356/140789 |
| _version_ | 1826112176997269504 |
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| author | Wong, Ezekiel Ngan Seng |
| author2 | Wang Han |
| author_facet | Wang Han Wong, Ezekiel Ngan Seng |
| author_sort | Wong, Ezekiel Ngan Seng |
| collection | NTU |
| description | The ability to navigate is a key aspect of mobile robots, especially so for autonomous ones. However, the presence of glare has always been an issue for them. As these autonomous mobile robots do not have human supervision, they navigate primarily through the use of their onboard cameras for environmental perception and localisation. With the presence of glare, this can seriously hamper their ability to navigate and in the worst case, cause accidents. As such, this paper will attempt to train a machine learning algorithm in order to rectify this issue. The model, when trained, will be able to segment portions of images containing glare, preventing the robot from using them in its navigational duties. |
| first_indexed | 2024-10-01T03:02:42Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/140789 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:02:42Z |
| publishDate | 2020 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1407892023-07-07T18:53:41Z Mobile robot navigation using deep learning Wong, Ezekiel Ngan Seng Wang Han School of Electrical and Electronic Engineering hw@ntu.edu.sg Engineering::Electrical and electronic engineering The ability to navigate is a key aspect of mobile robots, especially so for autonomous ones. However, the presence of glare has always been an issue for them. As these autonomous mobile robots do not have human supervision, they navigate primarily through the use of their onboard cameras for environmental perception and localisation. With the presence of glare, this can seriously hamper their ability to navigate and in the worst case, cause accidents. As such, this paper will attempt to train a machine learning algorithm in order to rectify this issue. The model, when trained, will be able to segment portions of images containing glare, preventing the robot from using them in its navigational duties. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-06-02T03:38:33Z 2020-06-02T03:38:33Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/140789 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Wong, Ezekiel Ngan Seng Mobile robot navigation using deep learning |
| title | Mobile robot navigation using deep learning |
| title_full | Mobile robot navigation using deep learning |
| title_fullStr | Mobile robot navigation using deep learning |
| title_full_unstemmed | Mobile robot navigation using deep learning |
| title_short | Mobile robot navigation using deep learning |
| title_sort | mobile robot navigation using deep learning |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/140789 |
| work_keys_str_mv | AT wongezekielnganseng mobilerobotnavigationusingdeeplearning |