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Drivable region detection for autonomous robots applied to South African underground mining
Includes bibliographical references.
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| Main Author: | |
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Computer Science
2014
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| _version_ | 1867613310992515072 |
|---|---|
| access_status_str | Open Access |
| author | Falola, Omowunmi Elizabeth |
| author2 | Bagula, Antoine |
| author_browse | Bagula, Antoine Falola, Omowunmi Elizabeth |
| author_facet | Bagula, Antoine Falola, Omowunmi Elizabeth |
| author_sort | Falola, Omowunmi Elizabeth |
| collection | Thesis |
| description | Includes bibliographical references. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/10492 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:34:06.076Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2014 |
| publishDateRange | 2014 |
| publishDateSort | 2014 |
| publisher | Department of Computer Science |
| publisherStr | Department of Computer Science |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/10492 Drivable region detection for autonomous robots applied to South African underground mining Falola, Omowunmi Elizabeth Bagula, Antoine Computer Science Includes bibliographical references. This dissertation focuses on enhancing autonomous robots' capability to identify drivable regions in underground terrains. A system model that compares the drivability analysis of underground terrains using the entropy model and statistical region merging (SRM) was developed, with a view to presenting an analysis of 2D and 3D results. The approach involves standard image-processing techniques, such as colour and texture feature extraction and region segmentation for underground image classification. A probabilistic method based on the local entropy was employed. The entropy is measured within a fixed window on each frame in order to compute features used in the segmentation process. This research compares the results obtained from the entropy method and SRM approach. Performance evaluation is carried out to provide useful qualitative and quantitative conclusions. 2014-12-29T05:04:51Z 2014-12-29T05:04:51Z 2012 Master Thesis Masters MSc http://hdl.handle.net/11427/10492 eng application/pdf Department of Computer Science Faculty of Science University of Cape Town |
| spellingShingle | Computer Science Falola, Omowunmi Elizabeth Drivable region detection for autonomous robots applied to South African underground mining |
| thesis_degree_str | Master's |
| title | Drivable region detection for autonomous robots applied to South African underground mining |
| title_full | Drivable region detection for autonomous robots applied to South African underground mining |
| title_fullStr | Drivable region detection for autonomous robots applied to South African underground mining |
| title_full_unstemmed | Drivable region detection for autonomous robots applied to South African underground mining |
| title_short | Drivable region detection for autonomous robots applied to South African underground mining |
| title_sort | drivable region detection for autonomous robots applied to south african underground mining |
| topic | Computer Science |
| url | http://hdl.handle.net/11427/10492 |
| work_keys_str_mv | AT falolaomowunmielizabeth drivableregiondetectionforautonomousrobotsappliedtosouthafricanundergroundmining |