02465nas a2200217 4500008004500000245006700045210006600112260002800178300001600206520181400222653001202036653001302048100001702061700001702078700001702095700001402112700001802126700002002144700001502164856006802179 2016 engldsh 00aReflex Control of the Pisa/IIT SoftHand during Object Slippage0 aReflex Control of the PisaIIT SoftHand during Object Slippage aStockholm, SwedenbIEEE a1972 - 19793 a

In this work, to guarantee the Pisa/IIT SoftHand’s

grasp robustness against slippage, three reflex control modes,

namely Current, Pose and Impedance, are implemented and

experimentally evaluated. Towards this objective, ThimbleSense

fingertip sensors are designed and integrated into the thumb

and middle fingers of the SoftHand for real-time detection and

control of the slippage. Current reflex regulates the restoring

grasp forces of the hand by modulating the motor’s current

profile according to an update law. Pose and Impedance reflex

modes instead replicate this behaviour by implementing an

impedance control scheme. The difference between the two

latter is that the stiffness gain in Impedance reflex mode is

being varied in addition to the hand pose, as a function of

the slippage on the fingertips. Experimental setup also includes

a seven degrees-of-freedom robotic arm to realize consistent

trajectories (e.g. lifting) among three control modes for the sake

of comparison. Different test objects are considered to evaluate

the efficacy of the proposed reflex modes in our experimental

setup. Results suggest that task-appropriate restoring forces

can be achieved using Impedance reflex due to its capability

in demonstrating instantaneous and rather smooth reflexive

behaviour during slippage. Preliminary experiments on five

healthy human subjects provide evidence on the similarity of the

control concepts exploited by the humans and the one realized

by the Impedance reflex, highlighting its potential in prosthetic

applications.

10aHaptics10aRobotics1 aAjoudani, A.1 aHocaoglu, E.1 aAltobelli, A1 aRossi, M.1 aBattaglia, E.1 aTsagarakis, N G1 aBicchi, A. uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=748734402477nas a2200181 4500008004500000245010600045210006900151260004900220300001600269520185200285653001202137653001302149100001702162700001302179700002002192700001502212856006802227 2015 engldsh 00aA Reduced-Complexity Description of Arm Endpoint Stiffness with Applications to Teleimpedance Control0 aReducedComplexity Description of Arm Endpoint Stiffness with App aHamburg, Germany, 28 Sept - 2 Oct 2015bIEEE a1017 - 10233 a

Effective and stable execution of a remote task in an uncertain environment requires that the task force and position trajectories of the slave robot be appropriately commanded. To achieve this goal, in teleimpedance control, a reference command which consists of the stiffness and position profiles of the master is computed and realized by the compliant slave robot in real-time. This highlights the need for a suitable and computationally efficient tracking of the human limb stiffness profile in real-time. In this direction, based on the observations in human neuromotor control which give evidence on the predominant use of the arm configuration in directional adjustments of the endpoint stiffness profile, and the role of muscular co-activations which contribute to a coordinated stiffening of the task stiffness in all directions, we propose a novel and computationally efficient model of the arm endpoint stiffness behaviour. With the purpose of real-time tracking of the human arm kinematics, an arm triangle is introduced using three body markers at the shoulder, elbow and wrist joints. In addition, a co-contraction index is defined using muscular activities of a dominant antagonistic muscle pair. Calibration and identification of the model parameters are carried out experimentally, using perturbation-based arm endpoint stiffness measurements in different arm configurations and co-contraction levels of the chosen muscles. Results of this study suggest that the proposed model enables the master to naturally execute a remote task by modulating the direction of the major axes of the endpoint stiffness and its volume using arm configuration and the co-ativation of the involved muscles, respectively.

10aHaptics10aRobotics1 aAjoudani, A.1 aFang, C.1 aTsagarakis, N G1 aBicchi, A. uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=735349500525nas a2200145 4500008003900000245007000039210006300109260003000172300001600202653001300218100001700231700002000248700001500268856009600283 2015 d00aOn the Role of Robot Configuration in Cartesian Stiffness Control0 aRole of Robot Configuration in Cartesian Stiffness Control aSeattle, USA, 25 - 30 May a1010 - 101610aRobotics1 aAjoudani, A.1 aTsagarakis, N G1 aBicchi, A. uhttp://95.110.227.16/publications/role-robot-configuration-cartesian-stiffness-control.html