00587nas a2200193 4500008004100000245011000041210006900151260001200220490000700232653001200239653001300251100001100264700001300275700001700288700001300305700001100318700001500329856004900344 2017 eng d00aAsymmetric Bimanual Coordinate Control of Dual-Arm Exoskeleton Robots for Human Cooperative Manipulations0 aAsymmetric Bimanual Coordinate Control of DualArm Exoskeleton Ro c11/20170 v3410aHaptics10aRobotics1 aLi, Z.1 aChen, Z.1 aAjoudani, A.1 aYang, C.1 aSu, C.1 aBicchi, A. uhttps://ieeexplore.ieee.org/document/810334002059nas a2200193 4500008004100000245007500041210006900116260001200185300001200197490000600209520150800215653001201723653001301735100001301748700001701761700001501778700002301793856004901816 2017 eng d00aOnline Model Based Estimation of Complete Joint Stiffness of Human Arm0 aOnline Model Based Estimation of Complete Joint Stiffness of Hum c01/2018 a84 - 910 v33 a

The endpoint stiffness of the human arm has been long recognized as a key component ensuring the quasi-static stability of the arm physical interactions with the external world. Similarly, the understanding of the joint stiffness behavior can provide complementary insights, e.g., on the underlying stiffness regulation principles across different joints including the nullspace stiffness profiles. Traditionally, the experimental modeling and estimation of the human arm joint stiffness is achieved by the transformation of the identified arm endpoint stiffness to the joint coordinates. Due to the underlying kinematic redundancy, the obtained joint stiffness matrix is rank-deficient which implies that the information in the joint stiffness matrix is incomplete. While in robotics applications this issue can be addressed by designing a desired nullspace stiffness behavior through appropriate projections, the use of a similar technique in the identification of human joint stiffness profile is meaningless. Hence, the first objective of this work is to address this issue by developing a novel technique to identify the complete and physiologically meaningful joint stiffness of human arm. Second, we present a model-based online estimation technique to estimate the seven-dimensional complete joint stiffness in various arm poses and activation levels of the two dominant arm muscles that correspond to the geometric and volume modifications of the joint stiffness profile, respectively.

10aHaptics10aRobotics1 aFang, C.1 aAjoudani, A.1 aBicchi, A.1 aTsagarakis, N., G. uhttp://ieeexplore.ieee.org/document/7990237/02465nas 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=748734405694nas a2200193 4500008004500000245008600045210006900131260004300200300001200243520507000255653001205325653001305337100001405350700001705364700001905381700001705400700001505417856006805432 2015 engldsh 00aElectromyographic Mapping of Finger Stiffness in Tripod Grasp: a Proof of Concept0 aElectromyographic Mapping of Finger Stiffness in Tripod Grasp a  aSingapore, 11 – 14 August 2015bIEEE a181-1863 a

Effective execution of a manipulation task using prosthetic or robotic hands requires that the motion and the impedance profiles of the fingers be appropriately commanded. This, however, brings some design and control challenges regarding the individual planning and realization of the finger motion and stiffnesstrajectories. It appears that the central nervous system solves for this complexity in an effective and coordinated manner which has been well-recognized under the concept of hand synergies. While the exploitation of this concept in kinematic coordinates has lead to the development of several successful robotic designs and control strategies, its extension to dynamic coordinates, such as coordinated stiffening of the fingers, remains to be investigated. Indeed, in this study we provide preliminary evidence on the existence of such coordinated stiffening patterns in human fingers and establish initial steps towards a real-time and effective modelling of the finger stiffness in a tripod grasp. To achieve this goal, the endpoint stiffness of the thumb, index and middle fingers of five healthy subjects are experimentally identified and correlated with the electromyography (EMG) signals recorded from a dominant antagonistic pair of the forearm muscles. Our findings suggest that: i) the magnitude of thestiffness ellipses at the fingertips grows in a coordinated way, subsequent to the co-contraction of the forearm muscles; ii) the length of the ellipses' axes appears to have a nearly linear relationship with the co-contraction level of the antagonistic muscle pair.

10aHaptics10aRobotics1 aRossi, M.1 aAltobelli, A1 aGodfrey, S. B.1 aAjoudani, A.1 aBicchi, A. uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=728119602477nas 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=735349500546nas a2200169 4500008003900000245005900039210005900098260002300157300001700180653001200197653001300209100001500222700001700237700001700254700001500271856009000286 2014 d00aActive gathering of frictional properties from objects0 aActive gathering of frictional properties from objects aChicago, USAbIEEE a3982 - 3987 10aHaptics10aRobotics1 aRosales, C1 aAjoudani, A.1 aGabiccini, M1 aBicchi, A. uhttp://95.110.227.16/publications/active-gathering-frictional-properties-objects.html00561nas a2200181 4500008003900000245005600039210005500095260001600150653001200166653001300178100001900191700001700210700001600227700002000243700001500263700001500278856008600293 2014 d00aExploring haptic feedback for the Pisa/IIT SoftHand0 aExploring haptic feedback for the PisaIIT SoftHand aHouston, TX10aHaptics10aRobotics1 aGodfrey, S. B.1 aAjoudani, A.1 aBianchi, M.1 aCatalano, M. G.1 aGrioli, G.1 aBicchi, A. uhttp://95.110.227.16/publications/exploring-haptic-feedback-pisaiit-softhand.html00647nas a2200205 4500008004100000245009600041210006900137300001400206490000600220653001200226653001300238100001700251700001900268700002000287700001600307700001500323700002000338700001500358856006800373 2014 eng d00aExploring Teleimpedance and Tactile Feedback for Intuitive Control of the Pisa/IIT SoftHand0 aExploring Teleimpedance and Tactile Feedback for Intuitive Contr a203 - 2150 v710aHaptics10aRobotics1 aAjoudani, A.1 aGodfrey, S. B.1 aCatalano, M. G.1 aBianchi, M.1 aGrioli, G.1 aTsagarakis, N G1 aBicchi, A. uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=675555402577nas a2200241 4500008003900000245009300039210006900132260004200201300001400243520183800257653001202095653001302107100001702120700001102137700001402148700001602162700001902178700001502197700002002212700001502232700002002247856006802267 2014 d00aManipulation Framework for Compliant Humanoid COMAN: Application to a Valve Turning Task0 aManipulation Framework for Compliant Humanoid COMAN Application  aMadrid, Spain, November 18 - 20bIEEE a664 - 6703 a

With the purpose of achieving a desired interaction performance for our compliant humanoid robot (COMAN), in this paper we propose a semi-autonomous control framework and evaluate it experimentally in a valve turning setup. The control structure consists of various modules and interfaces to identify the valve, locate the robot in front of it and perform the manipulation. The manipulation module implements four motion primitives (Reach, Grasp, Rotate and Disengage) and realizes the corresponding desired impedance profile for each phase to accomplish the task. In this direction, to establish a stable and compliant contact between the valve and the robot hands, while being able to generate the sufficient rotational torques depending on the valve's friction, Rotate incorporates a novel dual-arm impedance control technique to plan and realize a task-appropriate impedance profile. Results of the implementation of the proposed control framework are firstly evaluated in simulation studies using Gazebo. Subsequent experimental results highlight the efficiency of the proposed impedance planning and control in generation of the required interaction forces to accomplish the task.

10aHaptics10aRobotics1 aAjoudani, A.1 aLee, J1 aRocchi, A1 aFerrati, M.1 aHoffman, Mingo1 aSettimi, A1 aCaldwell, D. G.1 aBicchi, A.1 aTsagarakis, N G uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=704143402710nas a2200193 4500008003900000245011400039210007100153260004700224300001600271520205600287653001202343653001302355100001702368700002002385700001102405700001702416700001502433856006802448 2014 d00aNatural Redundancy Resolution in Dual-Arm Manipulation using Configuration Dependent Stiffness (CDS) Control0 aNatural Redundancy Resolution in DualArm Manipulation using Confi aHong Kong, May 31 2014-June 7 2014 bIEEE a1480 - 14863 a

Incorporation of human motor control principles in the motion control architectures for humanoid robots or assistive and prosthesis devices will permit these systems not only to look anthropomorphic and natural at the body ware level but also to generate natural motion profiles resembling those executed by humans during manipulation and locomotion. In this work, relying on the observations on human bimanual coordination, a novel realtime motion control strategy is proposed to regulate the desired Cartesian stiffness profile during the execution of bimanual tasks. The novelty of the proposed control scheme relies on the use of common mode stiffness (CMS) and configuration dependent stiffness (CDS) to regulate the size and directionality of the task space stiffness ellipsoid. Thanks to the CDS control, the proposed scheme is not only proved to be effective in regulating the desired stiffness ellipsoid but also permits to resolve the manipulator redundancy in a natural manner. The effectiveness of the controller is evaluated in an experimental setup in which two cooperating robotic arms are executing an assembly task. Experimental results demonstrate that the proposed dual-arm CDS-CMS controller is effective in tracking the desired stiffness ellipsoids as well as in producing human-like natural motions for the two robotic arms.

10aHaptics10aRobotics1 aAjoudani, A.1 aTsagarakis, N G1 aLee, J1 aGabiccini, M1 aBicchi, A. uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=694525200512nas a2200181 4500008004100000245005200041210004900093260003500142300001000177653001200187653001300199100001900212700001700231700002000248700001500268700001500283856003200298 2013 eng d00aA synergy-driven approach to a myoelectric hand0 asynergydriven approach to a myoelectric hand aJune 24-26, 2013, Seattle, WA. a1 - 610aHaptics10aRobotics1 aGodfrey, S. B.1 aAjoudani, A.1 aCatalano, M. G.1 aGrioli, G.1 aBicchi, A. u10.1109/ICORR.2013.6650377 00647nas a2200193 4500008004100000245006700041210006600108260003100174300001600205653001200221653001300233100001700246700001900263700002000282700001500302700002000317700001500337856010100352 2013 eng d00aTeleimpedance Control of a Synergy-Driven Anthropomorphic Hand0 aTeleimpedance Control of a SynergyDriven Anthropomorphic Hand aTokyo, JapancNovember 3-7 a1985 - 199110aHaptics10aRobotics1 aAjoudani, A.1 aGodfrey, S. B.1 aCatalano, M. G.1 aGrioli, G.1 aTsagarakis, N G1 aBicchi, A. uhttp://95.110.227.16/publications/teleimpedance-control-synergy-driven-anthropomorphic-hand.html