00691nas a2200169 4500008004100000245013800041210006900179260001200248490003800260100001300298700001800311700001600329700002000345700001500365700001500380856012600395 2019 eng d00aRelaying the High-Frequency Contents of TactileFeedback to Robotic Prosthesis Users: Design,Filtering, Implementation, and Validation0 aRelaying the HighFrequency Contents of TactileFeedback to Roboti c01/20190 vVolume: 4 , Issue: 2 , April 20191 aFani, S.1 aDi Blasio, K.1 aBianchi, M.1 aCatalano, M. G.1 aGrioli, G.1 aBicchi, A. uhttps://www.centropiaggio.unipi.it/publications/relaying-high-frequency-contents-tactilefeedback-robotic-prosthesis-users01636nas a2200181 4500008003900000245008500039210006900124260007100193520094800264653001201212100001801224700001801242700001601260700002001276700001501296700002101311856012201332 2017 d00aThe Rice Haptic Rocker: skin stretch haptic feedback with the Pisa/IIT SoftHand 0 aRice Haptic Rocker skin stretch haptic feedback with the PisaIIT aFürstenfeldbruck (Munich), Germany, June 6-9, 2017bIEEEc06/20173 a

Myoelectric prostheses have seen increased application in clinical practice and research, due to their potential for good functionality and versatility. Yet, myoelectric prostheses still suffer from a lack of intuitive control and haptic feedback, which can frustrate users and lead to abandonment. To address this problem, we propose to convey proprioceptive information for a prosthetic hand with skin stretch using the Rice Haptic Rocker. This device was integrated with the myo-controlled version of Pisa/IIT SoftHand and a size discrimination test with 18 able bodied subjects was performed to evaluate the effectiveness of the proposed approach. Results show that the Rice Haptic Rocker can be successfully used to convey proprioceptive information. A Likert survey was also presented to the experiment participants, who evaluated the integrated setup as easy to use and effective in conveying proprioception.

10aHaptics1 aBattaglia, E.1 aClark, J., P.1 aBianchi, M.1 aCatalano, M. G.1 aBicchi, A.1 aO'Malley, M., K. uhttps://www.centropiaggio.unipi.it/publications/rice-haptic-rocker-skin-stretch-haptic-feedback-pisaiit-softhand.html01805nas a2200217 4500008003900000020002300039245009300062210006900155260004300224520111600267653001301383100002101396700001601417700001701433700001901450700002001469700001501489700001901504700001501523856004901538 2016 d a978-1-5090-4718-5 00aRobust Optimization of System Compliance for Physical Interaction in Uncertain Scenarios0 aRobust Optimization of System Compliance for Physical Interactio aCancun, Mexico, 15-17 Nov. 2016 bIEEE3 a

Compliance in robot design and control is often introduced to improve the robot performance in tasks where interaction with environment or human is required. However a rigorous method to choose the correct level of compliance is still not available. In this work we use robust optimization as a tool to select the optimal compliance value in a robotenvironment interaction scenario under uncertainties. We propose an approach that can be profitably applied on a variety of tasks, e.g.manipulation tasks or locomotion tasks. The aim is to minimize the forces of interaction considering model constraints and uncertainties. Numerical results show that: i) in case of perfect knowledge of the environment stiff robots behave better in terms of force minimization, ii) in case of uncertainties the optimal stiffness of the robot is lower than the previous case and optimal solutions provide a faster task accomplishment, iii) the optimal stiffness decreases as a function of the uncertainty measure. Experiments are carried out in a realistic set-up in case of bi-manual object handover.

10aRobotics1 aGasparri, G., M.1 aFabiani, F.1 aGarabini, M.1 aPallottino, L.1 aCatalano, M. G.1 aGrioli, G.1 aPersichini, R.1 aBicchi, A. uhttp://ieeexplore.ieee.org/document/7803381/01977nas a2200217 4500008004100000245007200041210006800113260003900181300001400220520126700234653001301501100001501514700002001529700001401549700002001563700001501583700001501598700001701613700001501630856011401645 2009 eng d00aA Rough-Terrain, Casting Robot for the ESA Lunar Robotics Challenge0 aRoughTerrain Casting Robot for the ESA Lunar Robotics Challenge aSt. Louis MO USAcOctober, 11 - 15 a3336-33423 a

This paper describes the design and implementation of DAVID, a lunar vehicle developed for the European Space Agency (ESA) Lunar Robotics Challenge, presenting severe terrain negotiation and sample acquisition challenges. We discuss in some detail two of the main innovative aspects of our entry to the challenge, i.e. the locomotion system and the sample acquisition system. Motivated by the challenge specifications, a range of different locomotion systems were considered, among which we chose a simple, rugged and effective wheeled system. We provide an account of the choice of five different types of wheels, which were designed, analyzed and experimentally tested in conditions similar to the challenge. The system eventually turned out to be very effective in negotiating 89% slopes of volcanic terrain on the challenge site, Mount Teide in Tenerife. To reduce the distance to be traveled on the difficult terrain and avoid risks in reaching the lowest parts of a crater, the vehicle was endowed with an innovative sample acquisition system, i.e. a casting manipulator. Casting manipulation is a technique in which the end-effector is thrown, the sample material is acquired, and the end-effector is retrieved using a light tether that acts as a

10aRobotics1 aAlicino, S1 aCatalano, M. G.1 aBonomo, F1 aBelo, F., A. W.1 aGrioli, G.1 aSchiavi, R1 aFagiolini, A1 aBicchi, A. uhttps://www.centropiaggio.unipi.it/publications/rough-terrain-casting-robot-esa-lunar-robotics-challenge.html