A connectionist architecture for view-independent grip-aperture computation.

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A self-organizing neural network architecture for learning human-object interactions (2017, methodology): “Similar odels have been tested in robotics, accomplishing the recognition f grip apertures, affordances, or hand action classification [3,4] .”
Neural and Computational Mechanisms of Action Processing: Interaction between Visual and Motor Representations. (2015, methodology): “Other models of this type have been tested in robotics, accomplishing for example the recognition of grip apertures, affordances, or hand action classiﬁcation (Prevete et al., 2008; Tessitore et al., 2010).”
Physiologically Inspired Model for the Visual Recognition of Transitive Hand Actions (2013, unknown): “For example, a body movement can be represented as a temporal sequence of body shapes (Giese and Poggio, 2003; Lange and Lappe, 2006; Prevete et al., 2008).”
From motor to sensory processing in mirror neuron computational modelling (2010, background): “Thus, substantive pre-processing of sensory inputs is in many cases required to converge on the same direct internal input from these different perspectives (see Prevete et al. 2008; Fleischer et al. 2009, for a precise computational analysis of view-independent mappings).”