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Interpreting and Predicting Tactile Signals via a Physics-Based and Data-Driven Framework
[article]
2020
arXiv
pre-print
High-density afferents in the human hand have long been regarded as essential for human grasping and manipulation abilities. In contrast, robotic tactile sensors are typically used to provide low-density contact data, such as center-of-pressure and resultant force. Although useful, this data does not exploit the rich information content that some tactile sensors (e.g., the SynTouch BioTac) naturally provide. This research extends robotic tactile sensing beyond reduced-order models through 1)
arXiv:2006.03777v1
fatcat:2isf44sgffdz7aj664ry3gvn3i