@article {3710, title = {Touch as an auxiliary proprioceptive cue for movement control}, journal = {Indian Journal of Pure and Applied Physics }, year = {2019}, author = {A. Moscatelli and M. Bianchi and S. Ciotti and G. C. Bettelani and C. V. Parise and F. Lacquaniti and A. Bicchi} } @article {3448, title = {Simplifying Telerobotics: Wearability and Teleimpedance Improves Human-Robot Interactions in Teleoperation}, journal = {IEEE Robotics Automation Magazine}, volume = {25}, year = {2018}, month = {March}, pages = {77-88}, keywords = {application fields, augmented teleoperation, Autonomous robots, communication, effective design, effective simplification, environmental constraints, feedback, Force feedback, fundamental requirement, haptic feedback devices, haptic interfaces, human workspace, human-robot interaction, human-robot interactions, human-robot interfaces, ideal scenario, integrated approach, integrated interface, integrated system, interaction forces, intuitive information exchange, Kinematics, KUKA lightweight robotic arm, lightweight design, manipulators, master, position control, reduced versions, Robot sensing systems, robotic devices, robotic hand-arm system, robotic manipulator, robotic teleoperation, simplified information exchange, slave robot, stiffness control, synergy, Task analysis, teleimpedance techniques, Telemedicine, teleoperator system, telerobotics, TI control, vision, wearability, wearable feedback, wearable hand/arm}, issn = {1070-9932}, doi = {10.1109/MRA.2017.2741579}, author = {S. Fani and S. Ciotti and M. G. Catalano and G. Grioli and A. Tognetti and G. Valenza and A. Ajoudani and M. Bianchi} } @conference {3683, title = {Touch-Based Grasp Primitives for Soft Hands: Applications to Human-to-Robot Handover Tasks and Beyond}, booktitle = {2018 IEEE International Conference on Robotics and Automation (ICRA)}, year = {2018}, author = {M. Bianchi and G. Averta and E. Battaglia and C. Rosales and M. Bonilla and A. Tondo and M. Poggiani and G. Santaera and S. Ciotti and M. G. Catalano and A. Bicchi} } @article {3217, title = {W-FYD: a Wearable Fabric-based Display for Haptic Multi-Cue Delivery and Tactile Augmented Reality}, journal = {IEEE Transactions on Haptics}, volume = {11}, year = {2018}, pages = {304 - 316}, chapter = {304}, abstract = {

Despite the importance of softness, there is no evidence of wearable haptic systems able to deliver controllable softness cues. Here, we present the Wearable Fabric Yielding Display (W-FYD), a fabric-based display for multi-cue delivery that can be worn on user{\textquoteright}s finger and enables, for the first time, both active and passive softness exploration. It can also induce a sliding effect under the finger-pad. A given stiffness profile can be obtained by modulating the stretching state of the fabric through two motors. Furthermore, a lifting mechanism allows to put the fabric in contact with the user{\textquoteright}s finger-pad, to enable passive softness rendering. In this paper, we describe the architecture of W-FYD, and a thorough characterization of its stiffness workspace, frequency response and softness rendering capabilities. We also computed device Just Noticeable Difference in both active and passive exploratory conditions, for linear and non-linear stiffness rendering as well as for sliding direction perception. The effect of device weight was also considered. Furthermore, performance of participants and their subjective quantitative evaluation in detecting sliding direction and softness discrimination tasks are reported. Finally, applications of W-FYD in tactile augmented reality for open palpation are discussed, opening interesting perspectives in many fields of human-machine interaction.

}, keywords = {Haptics, Robotics}, issn = {1939-1412}, doi = {10.1109/TOH.2017.2708717}, url = {http://ieeexplore.ieee.org/document/8003491/}, author = {S. Fani and S. Ciotti and E. Battaglia and A. Moscatelli and M. Bianchi} } @conference {3365, title = {From humans to robots: The role of cutaneous impairment in human environmental constraint exploitation to inform the design of robotic hands}, booktitle = {Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), 2017 9th International Congress on}, year = {2017}, note = {

This work has been awarded with the "Best Student Paper Award" and the "Best Paper in Session - Robotics"

}, pages = {179{\textendash}184}, publisher = {IEEE}, organization = {IEEE}, address = {Munich}, abstract = {

Human hands are capable of a variety of movements, thanks to their extraordinary biomechanical structure and rely- ing on the richness of human tactile information. Recently, soft robotic hands have opened exciting possibilities and, at the same time, new issues related to planning and control. In this work, we propose to study human strategies in environmental constraint exploitation to grasp objects from a table. We have considered both the case where participants{\textquoteright} fingertips were free and with a rigid shell worn on them to understand the role of cutaneous touch. Main kinematic strategies were quantified and classified in an unsupervised manner. The principal strategies appear to be consistent in both experimental conditions, although cluster cardinality differs. Furthermore, as expected, tactile feedback improves both grasp precision and quality performance. Results opens interesting perspective for sensing and control of soft manipulators.

}, author = {G. Averta and C. Della Santina and E. Battaglia and S. Ciotti and V. Arapi and S. Fani and M. Bianchi} } @article {3216, title = {Postural Hand Synergies during Environmental Constraint Exploitation}, journal = {Fronters in Neurorobotics}, year = {2017}, month = {08/2017}, abstract = {

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.

}, keywords = {Haptics, Robotics}, doi = {https://doi.org/10.3389/fnbot.2017.00041}, url = {https://www.frontiersin.org/articles/10.3389/fnbot.2017.00041/full}, author = {C. Della Santina and M. Bianchi and G. Averta and S. Ciotti and V. Arapi and S. Fani and E. Battaglia and M. G. Catalano and M. Santello and A. Bicchi} } @conference {3726, title = {Synergy-driven performance enhancement of vision-based 3D hand pose reconstruction}, booktitle = {Wireless mobile communication and healthcare : 6th International conference, MobiHealth 2016, Milan, Italy, November 14-16, 2016, Proceedings}, year = {2017}, doi = {10.1007/978-3-319-58877-3_42}, author = {S. Ciotti and E. Battaglia and I. Oikonomidis and A. Makris and A. Tsoli and A. Bicchi and A. A. Agyros and M. Bianchi} } @conference {3122, title = {Tactile Slip and Hand Displacement: Bending Hand Motion with Tactile Illusions}, booktitle = {IEEE World Haptic Conference}, year = {2017}, note = {

\ This work is supported in part by the European Research Council under the Advanced Grant SoftHands {\textquotedblleft}A Theory of Soft Synergies for a New Generation of Artificial Hands{\textquotedblright} no. ERC-291166, by the EU H2020 project {\textquotedblleft}SOFTPRO: Synergy-based Open-source Foundations and Technologies for Prosthetics and RehabilitatiOn{\textquotedblright} (no. 688857) and by the EU FP7 project (no. 601165), {\textquotedblleft}WEARable HAPtics for Humans and Robots (WEARHAP){\textquotedblright}. We thank Priscilla Balestrucci and Colleen P. Ryan for helpful comments and suggestions.

}, month = {06/2017}, publisher = {IEEE}, organization = {IEEE}, address = {F{\"u}rstenfeldbruck (Munich), Germany, June 6-9, 2017}, abstract = {

Touch provides an important cue to perceive the physical properties of the external objects. Recent studies showed that tactile sensation also contributes to our sense of hand position and displacement in perceptual tasks. In this study, we tested the hypothesis that, sliding our hand over a stationary surface, tactile motion may provide a feedback for guiding hand trajectory. We asked participants to touch a plate having parallel ridges at different orientations and to perform a self-paced, straight movement of the hand. In our daily-life experience, tactile slip motion is equal and opposite to hand motion. Here, we used a well-established perceptual illusion to dissociate, in a controlled manner, the two motion estimates. According to previous studies, this stimulus produces a bias in the perceived direction of tactile motion, predicted by tactile flow model. We showed a systematic deviation in the movement of the hand towards a direction opposite to the one predicted by tactile flow, supporting the hypothesis that touch contributes to motor control of the hand. We suggested a model where the perceived hand motion is equal to a weighted sum of the estimate from classical proprioceptive cues (e.g., from musculoskeletal system) and the estimate from tactile slip.

}, keywords = {Haptics}, author = {M. Bianchi and A. Moscatelli and S. Ciotti and G. C. Bettelani and F. Fioretti and F. Lacquaniti and A. Bicchi} } @article {2866, title = {A Multi-Modal Sensing Glove for Human Manual-Interaction Studies}, journal = {Electronics}, volume = { 5}, year = {2016}, note = {

This work is supported in part by the European Research Council under the Advanced Grant {\textquotedblleft}SoftHands: A Theory of Soft Synergies for a New Generation of Artificial Hands{\textquotedblright} (No. ERC-291166), by the EU H2020 projects {\textquotedblleft}SoftPro: Synergy-based Open-source Foundations and Technologies for Prosthetics and RehabilitatiOn{\textquotedblright} (No. 688857) and {\textquotedblleft}SOMA: Soft Manipulation{\textquotedblright} (No. 64559) and by the EU FP7 project (No. 601165) {\textquotedblleft}WEARable HAPtics for Humans and Robots (WEARHAP){\textquotedblright}.

}, abstract = {

We present an integrated sensing glove that combines two of the most visionary wearable sensing technologies to provide both hand posture sensing and tactile pressure sensing in a unique, lightweight, and stretchable device. Namely, hand posture reconstruction employs Knitted Piezoresistive Fabrics that allows us to measure bending. From only five of these sensors (one for each finger) the full hand pose of a 19 degrees of freedom (DOF) hand model is reconstructed leveraging optimal sensor placement and estimation techniques. To this end, we exploit a-priori information of synergistic coordination patterns in grasping tasks. Tactile sensing employs a piezoresistive fabric allowing us to measure normal forces in more than 50 taxels spread over the palmar surface of the glove. We describe both sensing technologies, report on the software integration of both modalities, and describe a preliminary evaluation experiment analyzing hand postures and force patterns during grasping. Results of the reconstruction are promising and encourage us to push further our approach with potential applications in neuroscience, virtual reality, robotics and tele-operation.

}, keywords = {Haptics}, doi = {10.3390/electronics5030042}, url = {http://www.mdpi.com/2079-9292/5/3/42/pdf}, author = {M. Bianchi and R. Haschke and G. B{\"u}scher and S. Ciotti and N. Carbonaro and A. Tognetti} } @article {2867, title = {A Synergy-Based Optimally Designed Sensing Glove for Functional Grasp Recognition}, journal = {Sensors}, volume = {16}, year = {2016}, abstract = {

Achieving accurate and reliable kinematic hand pose reconstructions represents a challenging task. The main reason for this is the complexity of hand biomechanics, where several degrees of freedom are distributed along a continuous deformable structure. Wearable sensing can represent a viable solution to tackle this issue, since it enables a more natural kinematic monitoring. However, the intrinsic accuracy (as well as the number of sensing elements) of wearable hand pose reconstruction (HPR) systems can be severely limited by ergonomics and cost considerations. In this paper, we combined the theoretical foundations of the optimal design of HPR devices based on hand synergy information, i.e., the inter-joint covariation patterns, with textile goniometers based on knitted piezoresistive fabrics (KPF) technology, to develop, for the first time, an optimally-designed under-sensed glove for measuring hand kinematics. We used only five sensors optimally placed on the hand and completed hand pose reconstruction (described according to a kinematic model with 19 degrees of freedom) leveraging upon synergistic information. The reconstructions we obtained from five different subjects were used to implement an unsupervised method for the recognition of eight functional grasps, showing a high degree of accuracy and robustness.

}, keywords = {Haptics}, doi = {10.3390/s16060811}, url = {http://www.mdpi.com/1424-8220/16/6/811}, author = {S. Ciotti and E. Battaglia and N. Carbonaro and A. Bicchi and A. Tognetti and M. Bianchi} } @conference {2723, title = {A Wearable Fabric-based Display for Haptic Multi-Cue Delivery}, booktitle = {IEEE Haptics Symposium}, year = {2016}, publisher = {IEEE}, organization = {IEEE}, address = {Philadelphia, USA, April 8-11, 2016}, abstract = {

Softness represents one of the most informative

haptic properties, which plays a fundamental role in both

everyday tasks and more complex procedures. Thus, it is not

surprising that much effort has been devoted to designing haptic

systems able to suitably reproduce this information. At the

same time, wearability has gained an increasing importance as

a novel paradigm to enable a more effective and naturalistic

human robot interaction. Capitalizing upon our previous works

on grounded softness devices, in this paper we present the

Wearable Fabric Yielding Display (W-FYD), a fabric-based

tactile display for multi-cue delivery that can be worn by

user{\textquoteright}s finger. W-FYD enables to implement both passive and

active tactile exploration. Different levels of stiffness can be

reproduced by modulating the stretching state of a fabric

through two DC motors. An additional vertical degree of

freedom is implemented through a lifting mechanism, which

enables to convey softness stimuli to the user{\textquoteright}s finger pad.

Furthermore, a sliding effect on the finger can be also induced.

Experiments with humans show the effectiveness of W-FYD for

haptic multi-cue delivery.

}, keywords = {Haptics, Robotics}, doi = {10.1109/HAPTICS.2016.7463190}, url = {http://ieeexplore.ieee.org/search/searchresult.jsp?queryText=A\%20Wearable\%20Fabric-based\%20Display\%20for\%20Haptic\%20Multi-Cue\%20Delivery\&newsearch=true}, author = {M. Bianchi and E. Battaglia and M. Poggiani and S. Ciotti and A. Bicchi} }