02171nas a2200217 4500008004100000245009500041210006900136260001200205490001700217520144600234653001301680100001701693700001801710700001701728700001601745700001801761700001501779700002001794700001501814856012401829 2018 eng d00aDecentralized Trajectory Tracking Control for Soft Robots Interacting with the Environment0 aDecentralized Trajectory Tracking Control for Soft Robots Intera c06/20180 vEarly Access3 a

Despite the classic nature of the problem, trajectory

tracking for soft robots, i.e. robots with compliant elements

deliberately introduced in their design, still presents several

challenges. One of these is to design controllers which can

obtain sufficiently high performance while preserving the physical

characteristics intrinsic to soft robots. Indeed, classic control

schemes using high gain feedback actions fundamentally alter the

natural compliance of soft robots effectively stiffening them, thus

de facto defeating their main design purpose. As an alternative

approach, we consider here to use a low-gain feedback, while

exploiting feedforward components. In order to cope with the

complexity and uncertainty of the dynamics, we adopt a decentralized,

iteratively learned feedforward action, combined with

a locally optimal feedback control. The relative authority of the

feedback and feedforward control actions adapts with the degree

of uncertainty of the learned component. The effectiveness of the

method is experimentally verified on several robotic structures

and working conditions, including unexpected interactions with

the environment, where preservation of softness is critical for

safety and robustness.

10aRobotics1 aAngelini, F.1 aDella Santina1 aGarabini, M.1 aBianchi, M.1 aGasparri, G M1 aGrioli, G.1 aCatalano, M. G.1 aBicchi, A. uhttp://118699.obes.asia/publications/decentralized-trajectory-tracking-control-soft-robots-interacting-environment.html00514nas a2200145 4500008003900000245006800039210006800107260005400175653001300229100001800242700002400260700001500284700001100299856005800310 2018 d00aDynamic Control of Soft Robots Interacting with the Environment0 aDynamic Control of Soft Robots Interacting with the Environment a24 - 28 April 2018, Livorno, ItalybIEEEc07/201810aRobotics1 aDella Santina1 aKatzschmann, R., K.1 aBicchi, A.1 aRus, D uhttps://ieeexplore.ieee.org/abstract/document/840489502174nas 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=793043801687nas a2200205 4500008003900000245007900039210006900118260003800187300001400225520106500239653001301304100001601317700001401333700001801347700001701365700002001382700001501402700001501417856004901432 2017 d00aDesign, control and validation of the variable stiffness exoskeleton FLExo0 aDesign control and validation of the variable stiffness exoskele aLondon, UK, 17-20 July 2017bIEEE a539 - 5463 a

In this paper we present the design of a one degree of freedom assistive platform to augment the strength of upper limbs. The core element is a variable stiffness actuator, closely reproducing the behavior of a pair of antagonistic muscles. The novelty introduced by this device is the analogy of its control parameters with those of the human muscle system, the threshold lengths. The analogy can be obtained from a proper tuning of the mechanical system parameters. Based on this, the idea is to control inputs by directly mapping the estimation of the muscle activations, e.g. via ElectroMyoGraphic(EMG) sensors, on the exoskeleton. The control policy resulting from this mapping acts in feedforward in a way to exploit the muscle-like dynamics of the mechanical device. Thanks to the particular structure of the actuator, the exoskeleton joint stiffness naturally results from that mapping. The platform as well as the novel control idea have been experimentally validated and the results show a substantial reduction of the subject muscle effort.

10aRobotics1 aMghames, S.1 aLaghi, M.1 aDella Santina1 aGarabini, M.1 aCatalano, M. G.1 aGrioli, G.1 aBicchi, A. uhttp://ieeexplore.ieee.org/document/8009304/01632nas a2200241 4500008003900000245006600039210006500105260004000170520094200210653001201152653001301164100001501177700001501192700001501207700001701222700001801239700001801257700002001275700001601295700001501311700001501326856004901341 2017 d00aDesign of an Under-Actuated Wrist Based on Adaptive Synergies0 aDesign of an UnderActuated Wrist Based on Adaptive Synergies aSingapore, 29 May-3 June 2017bIEEE3 a

An effective robotic wrist represents a key enabling element in robotic manipulation, especially in prosthetics. In this paper, we propose an under-actuated wrist system, which is also adaptable and allows to implement different under-actuation schemes. Our approach leverages upon the idea of soft synergies - in particular the design method of adaptive synergies - as it derives from the field of robot hand design. First we introduce the design principle and its implementation and function in a configurable test bench prototype, which can be used to demonstrate the feasibility of our idea. Furthermore, we report on results from preliminary experiments with humans, aiming to identify the most probable wrist pose during the pre-grasp phase in activities of daily living. Based on these outcomes, we calibrate our wrist prototype accordingly and demonstrate its effectiveness to accomplish grasping and manipulation tasks.

10aHaptics10aRobotics1 aCasini, S.1 aTincani, V1 aAverta, G.1 aPoggiani, M.1 aDella Santina1 aBattaglia, E.1 aCatalano, M. G.1 aBianchi, M.1 aGrioli, G.1 aBicchi, A. uhttp://ieeexplore.ieee.org/document/7989789/00664nas a2200169 4500008003900000245009600039210006900135260005300204653001300257100001800270700001400288700001700302700001500319700002000334700001500354856012500369 2017 d00aEstimating Contact Forces from Postural Measures in a class of Under-Actuated Robotic Hands0 aEstimating Contact Forces from Postural Measures in a class of U aVancouver, Canada, September 24–28, 2017bIEEE10aRobotics1 aDella Santina1 aPiazza, C1 aSantaera, G.1 aGrioli, G.1 aCatalano, M. G.1 aBicchi, A. uhttp://118699.obes.asia/publications/estimating-contact-forces-postural-measures-class-under-actuated-robotic-hands.html02408nas a2200241 4500008004100000245007300041210006900114260001200183520171500195653001201910653001301922100001801935700001601953700001501969700001501984700001401999700001302013700001802026700002002044700001602064700001502080856007102095 2017 eng d00aPostural Hand Synergies during Environmental Constraint Exploitation0 aPostural Hand Synergies during Environmental Constraint Exploita c08/20173 a

Humans are able to intuitively exploit the shape of an object and environmental constraints to achieve stable grasps and perform dexterous manipulations. In doing that, a vast range of kinematic strategies can be observed. However, in this work we formulate the hypothesis that such ability can be described in terms of a synergistic behavior in the generation of hand postures, i.e., using a reduced set of commonly used kinematic patterns. This is in analogy with previous studies showing the presence of such behavior in different tasks, such as grasping. We investigated this hypothesis in experiments performed by six subjects, who were asked to grasp objects from a flat surface. We quantitatively characterized hand posture behavior from a kinematic perspective, i.e., the hand joint angles, in both pre-shaping and during the interaction with the environment. To determine the role of tactile feedback, we repeated the same experiments but with subjects wearing a rigid shell on the fingertips to reduce cutaneous afferent inputs. Results show the persistence of at least two postural synergies in all the considered experimental conditions and phases. Tactile impairment does not alter significantly the first two synergies, and contact with the environment generates a change only for higher order Principal Components. A good match also arises between the first synergy found in our analysis and the first synergy of grasping as quantified by previous work. The present study is motivated by the interest of learning from the human example, extracting lessons that can be applied in robot design and control. Thus, we conclude with a discussion on implications for robotics of our findings.

10aHaptics10aRobotics1 aDella Santina1 aBianchi, M.1 aAverta, G.1 aCiotti, S.1 aArapi, V.1 aFani, S.1 aBattaglia, E.1 aCatalano, M. G.1 aSantello, M1 aBicchi, A. uhttps://www.frontiersin.org/articles/10.3389/fnbot.2017.00041/full01807nas a2200181 4500008003900000020002200039245008800061210006900149520124000218653001301458100001401471700001801485700001401503700001501517700002001532700001501552856005801567 2017 d a978-1-5386-2296-400aPreliminary results toward a naturally controlled multi-synergistic prosthetic hand0 aPreliminary results toward a naturally controlled multisynergist3 a

Robotic hands embedding human motor control principles in their mechanical design are getting increasing interest thanks to their simplicity and robustness, combined with good performance. Another key aspect of these hands is that humans can use them very effectively thanks to the similarity of their behavior with real hands. Nevertheless, controlling more than one degree of actuation remains a challenging task. In this paper, we take advantage of these characteristics in a multi-synergistic prosthesis. We propose an integrated setup composed of Pisa/IIT SoftHand 2 and a control strategy which simultaneously and proportionally maps the human hand movements to the robotic hand. The control technique is based on a combination of non-negative matrix factorization and linear regression algorithms. It also features a real-time continuous posture compensation of the electromyographic signals based on an IMU. The algorithm is tested on five healthy subjects through an experiment in a virtual environment. In a separate experiment, the efficacy of the posture compensation strategy is evaluated on five healthy subjects and, finally, the whole setup is successfully tested in performing realistic daily life activities.

10aRobotics1 aRossi, M.1 aDella Santina1 aPiazza, C1 aGrioli, G.1 aCatalano, M. G.1 aBicchi, A. uhttp://ieeexplore.ieee.org/abstract/document/8009437/02018nas a2200229 4500008004100000022001500041245010300056210006900159300001200228490000700240520132900247653001301576100001801589700001401607700002101621700001501642700002001657700001501677700001701692700001501709856006401724 2017 eng d a1070-9932 00aThe Quest for Natural Machine Motion: An Open Platform to Fast-Prototyping Articulated Soft Robots0 aQuest for Natural Machine Motion An Open Platform to FastPrototy a48 - 560 v243 a
Soft robots are one of the most significant recent evolutions in robotics. They rely on compliant physical structures purposefully designed to embody desired characteristics. Since their introduction, they have shown remarkable applicability in overcoming their rigid counterparts in such areas as interaction with humans, adaptability, energy efficiency, and maximization of peak performance. Nonetheless, we believe
that research on novel soft robot applications is still slowed by the difficulty in obtaining or developing a working soft robot structure to explore novel applications.
In this article, we present the Natural Machine Motion Initiative (NMMI), a modular open platform that aims to provide the scientific community with tools for fast and easy prototyping of articulated soft robots. Such a platform is composed of three main open hardware modules: the Qbmoves variable-stiffness actuators (VSAs) to build the main robotic structure, soft end effectors (EEs) to interact with the world, and a pool of application-specific add-ons. We also discuss many novel uses of the platform to rapidly prototype (RP) and test new robotic structures with original soft capabilities, and we propose NMMI- based experiments.
10aRobotics1 aDella Santina1 aPiazza, C1 aGasparri, G., M.1 aBonilla, M1 aCatalano, M. G.1 aGrioli, G.1 aGarabini, M.1 aBicchi, A. uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=785769201695nas a2200157 4500008004100000245007600041210006900117260004000186520118200226653001301408100001701421700001801438700001701456700001501473856004901488 2017 eng d00aTowards Minimum-Information Adaptive Controllers for Robot Manipulators0 aTowards MinimumInformation Adaptive Controllers for Robot Manipu aMay 24–26 2017, Seattle USAbIEEE3 a

The aim of this paper is to move a step in the direction of determining the minimum amount of information needed to control a robot manipulator within the framework of adaptive control. Recent innovations in the state of the art show how global asymptotic trajectory tracking can be achieved despite the presence of uncertainties in the kinematic and dynamic models of the robot. However, a clear distinction between
which parameters can be included among the uncertainties, and which parameters can not, has not been drawn yet. Since most of the adaptive control algorithms are built on linearly parameterized models, we propose to reformulate the problem as finding a procedure to determine whether and how a given dynamical system can be linearly parameterized with respect to a specific set of parameters.
Within this framework, we show how the trajectory tracking problem of a manipulator can be accomplished with the only knowledge of the number of joints of the manipulator. As an illustrative example, we present the end-effector trajectory tracking control of a robot initialized with the kinematic model of a different robot.

10aRobotics1 aMarcucci, T.1 aDella Santina1 aGabiccini, M1 aBicchi, A. uhttps://ieeexplore.ieee.org/document/796360201277nas a2200205 4500008004500000245005900045210005900104260002200163300001200185490007200197520062200269653001300891100001700904700001800921700001600939700002000955700001500975700001500990856006601005 2016 engldsh 00aSoft Robots that Mimic the Neuromusculoskeletal System0 aSoft Robots that Mimic the Neuromusculoskeletal System bSpringerc10/2016 a259-2630 vConverging Clinical and Engineering Research on Neurorehabilitation3 a

In motor control studies, the question on which
parameters human beings and animals control through their
nervous system has been extensively explored and discussed,
and several hypotheses proposed. It is widely acknowledged
that useful inputs in this problem could be provided by
developing artificial replication of the neuromusculoskeletal
system, to experiment different motor control hypothesis. In
this paper we present such device, which reproduces many of
the characteristics of an agonistic-antagonistic muscular pair
acting on a joint.

10aRobotics1 aGarabini, M.1 aDella Santina1 aBianchi, M.1 aCatalano, M. G.1 aGrioli, G.1 aBicchi, A. uhttp://link.springer.com/chapter/10.1007/978-3-319-46669-9_4501929nas a2200205 4500008003900000245012300039210006900162260003900231300001600270520124500286653001201531653001301543100001401556700001801570700002001588700001501608700001701623700001501640856006801655 2016 d00aSoftHand Pro-D: Matching Dynamic Content of Natural User Commands with Hand Embodiment for Enhanced Prosthesis Control0 aSoftHand ProD Matching Dynamic Content of Natural User Commands  aStockholm, Sweden, May 16-21bIEEE a3516 - 35233 a

State of the art of hand prosthetics is divided between simple and reliable gripper-like systems and sophisticate hi-tech poly-articular hands which tend to be complex both in their design and for the patient to operate. In this paper, we introduce the idea of decoding different movement intentions of the patient using the dynamic frequency content of the control signals in a natural way. We move a step further showing how this idea can be embedded in the mechanics of an underactuated soft hand by using only passive damping components.

In particular we devise a method to design the hand hardware to obtain a given desired motion. This method, that we call of the dynamic synergies, builds on the theory of linear descriptor systems, and is based on the division of the hand movement in a slow and a fast components. We use this method to evolve the design of the Pisa/IIT SoftHand in a prototype prosthesis which, while still having 19 degrees of freedom and just one motor, can move along two different synergistic directions of motion (and combinations of the two), to perform either a pinch or a power grasp. Preliminary experimental results are presented, demonstrating the effectiveness of the proposed design

10aHaptics10aRobotics1 aPiazza, C1 aDella Santina1 aCatalano, M. G.1 aGrioli, G.1 aGarabini, M.1 aBicchi, A. uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=748753201511nas a2200193 4500008003900000245004800039210004800087260004100135520094000176653001301116100001401129700001801143700002101161700002001182700001501202700001701217700001501234856006801249 2016 d00aToward an Adaptive Foot for Natural Walking0 aToward an Adaptive Foot for Natural Walking aCancun, Mexico, November 15-17, 20163 a

Many walking robot presented in literature stand
on rigid flat feet, with a few notable exceptions that embed
flexibility in their feet to optimize the energetic cost of walking.
This paper proposes a novel adaptive robot foot design, whose
main goal is to ease the task of standing and walking on uneven
terrains. After explaining the rationale behind our design
approach, we present the design of the SoftFoot, a foot able
to comply with uneven terrains and to absorb shocks thanks to
its intrinsic adaptivity, while still being able to rigidly support
the stance, maintaining a rather extended contact surface,
and effectively enlarging the equivalent support polygon. The
paper introduces the robot design and prototype and presents
preliminary validation and comparison versus a rigid flat foot
with comparable footprint and sole.

10aRobotics1 aPiazza, C1 aDella Santina1 aGasparri, G., M.1 aCatalano, M. G.1 aGrioli, G.1 aGarabini, M.1 aBicchi, A. uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=780342301295nas a2200169 4500008003900000020002200039245007900061210006900140260003400209520075400243653001300997100001401010700001801024700001501042700001901057856004901076 2015 d a978-1-4799-8736-800aCoordination of unmanned marine vehicles for asymmetric threats protection0 aCoordination of unmanned marine vehicles for asymmetric threats  aMay 18-21, Genoa, ItalybIEEE3 a

A coordination protocol for systems of unmanned marine vehicles is proposed for protection against asymmetric threats. The problem is first modelled in a game theoretic framework, as a potential game. Then an extension of existing learning algorithms is proposed to address the problem of tracking the possibly moving threat. The approach is evaluated in scenarios of different geometric complexity such as open sea, bay, and harbours. Performance of the approach is evaluated in terms of a security index that will allow us to obtain a tool for team sizing. The tool provides the minimum number of marine vehicles to be used in the system, given a desired security level to be guaranteed and the maximum threat velocity.

10aRobotics1 aNardi, S.1 aDella Santina1 aMeucci, D.1 aPallottino, L. uhttp://ieeexplore.ieee.org/document/7271413/01545nas a2200193 4500008003900000245007300039210006900112260004500181300001400226520093500240653001201175653001301187100001801200700001501218700002001233700001501253700001501268856006801283 2015 d00aDexterity augmentation on a synergistic hand: the Pisa/IIT SoftHand+0 aDexterity augmentation on a synergistic hand the PisaIIT SoftHan aSeoul, Korea, November 3 - 5, 2015bIEEE a497 - 5033 a
Soft robotics and under-actuation were recently demonstrated as good approaches for the implementation of humanoid robotic hands. Nevertheless, it is often difficult to increase the number of degrees of actuation of heavily under-actuated hands without compromising their intrinsic simplicity. In this paper we analyze the Pisa/IIT SoftHand and its underlying logic of adaptive synergies, and propose a method to double its number of degree of actuation, with a very reduced impact on its mechanical complexity. This new design paradigm is based on constructive exploitation of friction phenomena.
Based on this method, a novel prototype of under-actuated robot hand with two degrees of actuation is proposed, named Pisa/IIT SoftHand+. A preliminary validation of the prototype follows, based on grasping and manipulation examples of some objects.
10aHaptics10aRobotics1 aDella Santina1 aGrioli, G.1 aCatalano, M. G.1 aBrando, A.1 aBicchi, A. uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7363595