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 tactil
e 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 hands 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. Supplemental video: https://youtu.be/ndsxj659bkQ
We present thermopower $S$ and resistance $R$ measurements on GaAs-based mesoscopic two-dimensional electron gases (2DEGs) as functions of the electron density $n_s$. At high $n_s$ we observe good agreement between the measured $S$ and $S_{rm{MOTT}}$
, the Mott prediction for a non-interacting metal. As $n_s$ is lowered, we observe a crossover from Mott-like behaviour to that where $S$ shows strong oscillations and even sign changes. Remarkably, there are absolutely no features in $R$ corresponding to those in $S$. In fact, $R$ is devoid of even any universal conductance fluctuations. A statistical analysis of the thermopower oscillations from two devices of dissimilar dimensions suggest a universal nature of the oscillations. We critically examine whether they can be mesoscopic fluctuations of the kind described by Lesovik and Khmelnitskii in Sov. Phys. JETP. textbf{67}, 957 (1988).
