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Data-driven artificial and spiking neural networks for inverse kinematics in neurorobotics
Inverse kinematics is fundamental for computational motion planning. It is used to derive an appropriate state in a robot's configuration space, given a target position in task space. In this work, we investigate the performance of fully connected and residual artificial neural networks as well...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8767299/ https://www.ncbi.nlm.nih.gov/pubmed/35079712 http://dx.doi.org/10.1016/j.patter.2021.100391 |