Learning and Execution of Object Manipulation Tasks on Humanoid Robots
Equipping robots with complex capabilities still requires a great amount of effort. In this work, a novel approach is proposed to understand, to represent and to execute object manipulation tasks learned from observation by combining methods of data analysis, graphical modeling and artificial intell...
Uloženo v:
| Hlavní autor: | |
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| Médium: | Online |
| Jazyk: | angličtina |
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KIT Scientific Publishing
2021
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| Témata: | |
| On-line přístup: | 34213 |
| Tagy: |
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| Shrnutí: | Equipping robots with complex capabilities still requires a great amount of effort. In this work, a novel approach is proposed to understand, to represent and to execute object manipulation tasks learned from observation by combining methods of data analysis, graphical modeling and artificial intelligence. Employing this approach enables robots to reason about how to solve tasks in dynamic environments and to adapt to unseen situations. |
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