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Representing, learning, and controlling complex object interactions
We present a framework for representing scenarios with complex object interactions, where a robot cannot directly interact with the object it wishes to control and must instead influence it via intermediate objects. For instance, a robot learning to drive a car can only change the car’s pose indirec...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417403/ https://www.ncbi.nlm.nih.gov/pubmed/30956402 http://dx.doi.org/10.1007/s10514-018-9740-7 |