In this work, we report on the integrated sensorimotor control of the
Pisa/IIT SoftHand, an anthropomorphic soft robot hand designed around the
principle of adaptive synergies, with the BRL tactile fingertip (TacTip), a
soft biomimetic optical tactile sensor based on the human sense of touch. Our
focus is how a sense of touch can be used to control an anthropomorphic hand
with one degree of actuation, based on an integration that respects the hand's
mechanical functionality. We consider: (i) closed-loop tactile control to
establish a light contact on an unknown held object, based on the structural
similarity with an undeformed tactile image; and (ii) controlling the estimated
pose of an edge feature of a held object, using a convolutional neural network
approach developed for controlling other sensors in the TacTip family. Overall,
this gives a foundation to endow soft robotic hands with human-like touch, with
implications for autonomous grasping, manipulation, human-robot interaction and
prosthetics.
Authors: Nathan F. Lepora, Andrew Stinchcombe, Chris Ford, Alfred Brown, John Lloyd, Manuel G. Catalano, Matteo Bianchi, Benjamin Ward-Cherrier (University of Bristol)
