Enhancing robot perception using human teammates
In robotics research, perception is one of the most challenging tasks. In contrast to existing approaches that rely only on computer vision, we propose an alternative method for improving perception by learning from human teammates. To evaluate, we apply this idea to a door detection problem. A set...
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2013
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sg-smu-ink.sis_research-92362023-10-26T03:30:17Z Enhancing robot perception using human teammates OH, Jean SUPPE, Arne STENTZ, Anthony HEBERT, Martial In robotics research, perception is one of the most challenging tasks. In contrast to existing approaches that rely only on computer vision, we propose an alternative method for improving perception by learning from human teammates. To evaluate, we apply this idea to a door detection problem. A set of preliminary experiments has been completed using software agents with real vision data. Our results demonstrate that information inferred from teammate observations significantly improves the perception precision. 2013-05-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/8233 https://ink.library.smu.edu.sg/context/sis_research/article/9236/viewcontent/oh2013_aamas.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Robot perception Robot-human hybrid teams Artificial Intelligence and Robotics |
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Singapore Management University |
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SMU Libraries |
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Asia |
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Singapore Singapore |
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InK@SMU |
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English |
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Robot perception Robot-human hybrid teams Artificial Intelligence and Robotics |
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Robot perception Robot-human hybrid teams Artificial Intelligence and Robotics OH, Jean SUPPE, Arne STENTZ, Anthony HEBERT, Martial Enhancing robot perception using human teammates |
| description |
In robotics research, perception is one of the most challenging tasks. In contrast to existing approaches that rely only on computer vision, we propose an alternative method for improving perception by learning from human teammates. To evaluate, we apply this idea to a door detection problem. A set of preliminary experiments has been completed using software agents with real vision data. Our results demonstrate that information inferred from teammate observations significantly improves the perception precision. |
| format |
text |
| author |
OH, Jean SUPPE, Arne STENTZ, Anthony HEBERT, Martial |
| author_facet |
OH, Jean SUPPE, Arne STENTZ, Anthony HEBERT, Martial |
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OH, Jean |
| title |
Enhancing robot perception using human teammates |
| title_short |
Enhancing robot perception using human teammates |
| title_full |
Enhancing robot perception using human teammates |
| title_fullStr |
Enhancing robot perception using human teammates |
| title_full_unstemmed |
Enhancing robot perception using human teammates |
| title_sort |
enhancing robot perception using human teammates |
| publisher |
Institutional Knowledge at Singapore Management University |
| publishDate |
2013 |
| url |
https://ink.library.smu.edu.sg/sis_research/8233 https://ink.library.smu.edu.sg/context/sis_research/article/9236/viewcontent/oh2013_aamas.pdf |
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