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Robot End Effector Tracking Using Predictive Multisensory Integration
We propose a biologically inspired model that enables a humanoid robot to learn how to track its end effector by integrating visual and proprioceptive cues as it interacts with the environment. A key novel feature of this model is the incorporation of sensorimotor prediction, where the robot predict...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6198278/ https://www.ncbi.nlm.nih.gov/pubmed/30386227 http://dx.doi.org/10.3389/fnbot.2018.00066 |