00585nas a2200169 4500008003900000245010600039210006900145100002000214700002000234700001800254700001900272700001700291700001500308700001600323700002700339856004900366 2019 d00aComparison of Three Hand Pose Reconstruction Algorithms Using Inertial and Magnetic Measurement Units0 aComparison of Three Hand Pose Reconstruction Algorithms Using In1 aKieliba, P., J.1 aVeltink, P., H.1 aBaldi, Lisini1 aPratichizzo, D1 aSantaera, G.1 aBicchi, A.1 aBianchi, M.1 aVan Beijnum, B., J. F. uhttps://ieeexplore.ieee.org/document/862492902174nas a2200229 4500008004100000022001400041245007300055210006900128260001200197300001200209490000700221520152100228653001301749100001801762700001601780700001501796700001701811700002001828700001701848700001501865856006401880 2017 eng d a1070-993200aControlling Soft Robots: Balancing Feedback and Feedforward Elements0 aControlling Soft Robots Balancing Feedback and Feedforward Eleme c05/2017 a75 - 830 v243 a

Soft robots (SRs) represent one of the most significant recent evolutions in robotics. Designed to embody safe and natural behaviors, they rely on compliant physical structures purposefully designed to embody desirable and sometimes variable impedance characteristics. This article discusses the problem of controlling SRs. We start by observing that most of the standard methods of robotic control—e.g., high-gain robust control, feedback linearization, backstepping, and active impedance control—effectively fight against or even completely cancel the physical dynamics of the system, replacing them with a desired model. This defeats the purpose of introducing physical compliance. After all, what is the point of building soft actuators if we then make them stiff by control? An alternative to such approaches can be conceived by observing humans, who can obtain good motion accuracy and repeatability while maintaining the intrinsic softness of their bodies. In this article, we show that an anticipative model of human motor control, using a feedforward action combined with low-gain feedback, can be used to achieve human-like behavior. We present an implementation of such an idea that uses iterative learning control. Finally, we present the experimental results of the application of such learned anticipative control to a physically compliant robot. The control application achieves the desired behavior much better than a classical feedback controller used for comparison.

10aRobotics1 aDella Santina1 aBianchi, M.1 aGrioli, G.1 aAngelini, F.1 aCatalano, M. G.1 aGarabini, M.1 aBicchi, A. uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=793043802143nas a2200229 4500008004100000245007100041210006700112260001200179300001600191490000700207520149200214653001201706653001301718100001901731700001601750700001401766700001701780700001601797700001401813700001501827856007101842 2016 eng d00aThe Change in Fingertip Contact Area as a Novel Proprioceptive Cue0 aChange in Fingertip Contact Area as a Novel Proprioceptive Cue c05/2016 a1159–11630 v263 a

Humans, many animals, and certain robotic hands have deformable fingertip pads. Deformable pads have the advantage of conforming to the objects that are being touched, ensuring a stable grasp for a large range of forces and shapes. Pad deformations change with finger displacements during touch. Pushing a finger against an external surface typically provokes an increase of the gross contact area, potentially providing a relative motion cue, a situation comparable to looming in vision. The rate of increase of the area of contact also depends on the compliance of the object. Because objects normally do not suddenly change compliance, participants may interpret an artificially induced variation in compliance, which coincides with a change in the gross contact area, as a change in finger displacement, and consequently they may misestimate their finger’s position relative to the touched object. To test this, we asked participants to compare the perceived displacements of their finger while contacting an object varying pseudo-randomly in compliance from trial to trial. Results indicate a bias in the perception of finger displacement induced by the change in compliance, hence in contact area, indicating that participants interpreted the altered cutaneous input as a cue to proprioception. This situation highlights the capacity of the brain to take advantage of knowledge of the mechanical properties of the body and of the external environment.

10aHaptics10aRobotics1 aMoscatelli, A.1 aBianchi, M.1 aSerio, A.1 aTerekhov, A.1 aHayward, V.1 aErnst, M.1 aBicchi, A. uhttp://www.sciencedirect.com/science/article/pii/S096098221630134804167nas a2200229 4500008004500000245007700045210006900122260003400191300001000225520347300235653001203708653001303720100001503733700002103748700001703769700001603786700001303802700001503815700002003830700001903850856006803869 2015 engldsh 00aCharacterization of Nonlinear Finger Pad Mechanics for Tactile Rendering0 aCharacterization of Nonlinear Finger Pad Mechanics for Tactile R aChicago, USA, 22-25 June 2015 a63-683 a

The computation of skin forces and deformations for tactile rendering requires an accurate model of the extremely nonlinear behavior of the skin. In this work, we investigate the characterization of fingermechanics with the goal of designing accurate nonlinear models for tactile rendering. First, we describe a measurement setup that enables the acquisition of contact force and contact area in the context of controlled finger indentation experiments. Second, we describe an optimization procedure that estimates the parameters of strain-limiting deformation models that match best the acquired data. We show that the acquisition setup allows the measurement of force and area information with high repeatability, and the estimation method reaches nonlinear models that match the measured data with high accuracy.

10aHaptics10aRobotics1 aMiguel, E.1 aD'Angelo, M., L.1 aCannella, F.1 aBianchi, M.1 aMemeo, M1 aBicchi, A.1 aCaldwell, D. G.1 aOtaduy, M., A. uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=717769200863nas a2200241 4500008003900000245009000039210006900129260005200198300001200250490008500262653001200347653001300359100001900372700001600391700001400407700001500421700001300436700001700449700001600466700001400482700001500496856011000511 2014 d00aA change in the fingertip contact area induces an illusory displacement of the finger0 achange in the fingertip contact area induces an illusory displac aVersailles, France), June 2014bSpringer-Verlag a72 - 790 vLNCS - Free Preview Haptics: Neuroscience, Devices, Modeling, and Applications10aHaptics10aRobotics1 aMoscatelli, A.1 aBianchi, M.1 aSerio, A.1 aAtassi, Al1 aFani, S.1 aTerekhov, A.1 aHayward, V.1 aErnst, M.1 aBicchi, A. uhttp://95.110.227.16/publications/change-fingertip-contact-area-induces-illusory-displacement-finger.html00529nas a2200145 4500008004100000245007500041210006900116300001400185653001300199100001800212700001600230700001200246700001700258856010800275 2013 eng d00aCharacterization and Psychophysical Studies of an Air-Jet Lump Display0 aCharacterization and Psychophysical Studies of an AirJet Lump Di a156 - 16610aRobotics1 aGwilliam, J C1 aBianchi, M.1 aSu, L K1 aOkamura, A M uhttp://95.110.227.16/publications/characterization-and-psychophysical-studies-air-jet-lump-display.html00505nas a2200157 4500008004100000245005500041210005500096300001400151653001200165653001300177100001600190700001800206700001800224700001700242856008800259 2011 eng d00aCharacterization of an Air Jet Haptic Lump Display0 aCharacterization of an Air Jet Haptic Lump Display a3467-347010aHaptics10aRobotics1 aBianchi, M.1 aGwilliam, J C1 aDegirmenci, A1 aOkamura, A M uhttp://95.110.227.16/publications/characterization-air-jet-haptic-lump-display.html