@article {3621, title = {Learning From Humans How to Grasp: A Data-Driven Architecture for Autonomous Grasping With Anthropomorphic Soft Hands}, journal = {IEEE Robotics and Automation Letters}, volume = {4}, year = {2019}, month = {April}, pages = {1533-1540}, keywords = {Computer architecture, Control, Deep Learning in Robotics and Automation, Grasping, Learning for Soft Robots, Modeling, Natural Machine Motion, Neural networks, Robot sensing systems, Uncertainty, Videos}, issn = {2377-3766}, doi = {10.1109/LRA.2019.2896485}, author = {C. D. Santina and V. Arapi and G. Averta and F. Damiani and G. Fiore and A Settimi and M. G. Catalano and D. Bacciu and A. Bicchi and M. Bianchi} } @article {3677, title = {On the time-invariance properties of upper limb synergies}, journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering }, year = {2019}, month = {07/2019}, doi = {https://doi.org/10.1109/TNSRE.2019.2918311}, url = {https://www.ncbi.nlm.nih.gov/pubmed/31135365}, author = {G. Averta and G. Valenza and V. Catrambone and F. Barontini and E. P. Scilingo and A. Bicchi and M. Bianchi} } @conference {3721, title = {EEG Complexity Maps to Characterise Brain Dynamics during Upper Limb Motor Imagery}, booktitle = { Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS}, year = {2018}, doi = { 10.1109/EMBC.2018.8512912}, url = { https://ieeexplore.ieee.org/document/8512912}, author = {V. Catambrone and A. Greco and G. Averta and M. Bianchi and A. Bicchi and E. P. Scilingo and G. Valenza} } @conference {3722, title = {EEG Processing to Discriminate Transitive-Intransitive Motor Imagery Tasks: Preliminary Evidences using Support Vector Machines}, booktitle = {Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS}, year = {2018}, doi = {10.1109/EMBC.2018.8512239}, url = {https://zenodo.org/record/2559406$\#$.XTbl43ux9GM}, author = {V. Catrambone and A. Greco and G. Averta and M. Bianchi and N. Vanello and A. Bicchi and G. Valenza and E. P. Scilingo} } @article {3364, title = {Efficient Walking Gait Generation via Principal Component Representation of Optimal Trajectories: Application to a Planar Biped Robot With Elastic Joints}, journal = {IEEE Robotics and Automation Letters}, volume = {3}, year = {2018}, pages = {2299{\textendash}2306}, abstract = {

Recently, the method of choice to exploit robot dynamics for efficient walking is numerical optimization (NO). The main drawback in NO is the computational complexity, which strongly affects the time demand of the solution. Several strategies can be used to make the optimization more treatable and to efficiently describe the solution set. In this letter, we present an algorithm to encode effective walking references, generated offline via numerical optimization, extracting a limited number of principal components and using them as a basis of optimal motions. By combining these components, a good approximation of the optimal gaits can be generated at run time. The advantages of the presented approach are discussed, and an extensive experimental validation is carried out on a planar legged robot with elastic joints. The biped thus controlled is able to start and stop walking on a treadmill, and to control its speed dynamically as the treadmill speed changes.

}, author = {G M Gasparri and S. Manara and D. Caporale and G. Averta and M. Bonilla and H. Marino and M. G. Catalano and G. Grioli and M. Bianchi and A. Bicchi and M. Garabini} } @article {3447, title = {Incrementality and Hierarchies in the Enrollment of Multiple Synergies for Grasp Planning}, journal = {IEEE Robotics and Automation Letters}, volume = {3}, year = {2018}, month = {July}, pages = {2686-2693}, keywords = {19-DoF anthropomorphic hand, Biomechanics, common grasping tasks, compliant joint/mechanism, covariance matrices, experimental covariance matrix, Force, force distribution, grasp planning, Grasping, grippers, hand posture reconstruction, hand-object relative pose, incremental learning algorithm, Jacobian matrices, joint angle covariation patterns, learning (artificial intelligence), minimisation, multifingered hands, pose estimation, postural hand synergies, postural synergies, posture description, principal component analysis, reduced complexity representation, relative statistical weight, Robots, Solid modeling, synergy vectors, Task analysis}, doi = {10.1109/LRA.2018.2829027}, author = {G. Averta and F. Angelini and M. Bonilla and M. Bianchi and A. Bicchi} } @conference {3718, title = {On the role of postural synergies for grasp force generation and upper limb motion control}, booktitle = {International Conference on NeuroRehabilitation}, year = {2018}, url = {https://link.springer.com/chapter/10.1007/978-3-030-01845-0_69}, author = {G. Averta and F. Angelini and A. Bicchi and G. Valenza 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} } @conference {3106, title = {Design of an Under-Actuated Wrist Based on Adaptive Synergies}, booktitle = {IEEE International Conference of Robotics and Automation, ICRA2017}, year = {2017}, publisher = {IEEE}, organization = {IEEE}, address = {Singapore, 29 May-3 June 2017}, abstract = {

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.

}, keywords = {Haptics, Robotics}, doi = {10.1109/ICRA.2017.7989789}, url = {http://ieeexplore.ieee.org/document/7989789/}, author = {S. Casini and V. Tincani and G. Averta and M. Poggiani and C. Della Santina and E. Battaglia and M. G. Catalano and M. Bianchi and G. Grioli and A. Bicchi} } @conference {3387, title = {Design of an under-actuated wrist based on adaptive synergies}, booktitle = {Robotics and Automation (ICRA), 2017 IEEE International Conference on}, year = {2017}, pages = {6679{\textendash}6686}, publisher = {IEEE}, organization = {IEEE}, abstract = {

An effective robotic wrist represents a key en- abling 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 intro- duce 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.

}, author = {S. Casini and V. Tincani and G. Averta and M. Poggiani and C. Della Santina and E. Battaglia and M. G. Catalano and M. Bianchi and G. Grioli and A. Bicchi} } @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} } @article {3363, title = {Unvealing the principal modes of human upper limb movements through functional analysis}, journal = {Frontiers in Robotics and AI}, volume = {4}, year = {2017}, pages = {37}, abstract = {

The rich variety of human upper limb movements requires an extraordinary coordination of different joints according to specific spatio-temporal patterns. However, unvealing these motor schemes is a challenging task. Principal components have been often used for analogous purposes, but such an approach relies on hypothesis of temporal uncorrelation of upper limb poses in time. To overcome these limitations, in this work, we leverage on functional principal component analysis (fPCA). We carried out experiments with 7 subjects performing a set of most significant human actions, selected considering state-of-the-art grasp taxonomies and human kinematic workspace. fPCA results show that human upper limb trajectories can be reconstructed by a linear combination of few principal time-dependent functions, with a first component alone explaining around 60/70\% of the observed behaviors. This allows to infer that in daily living activities humans reduce the complexity of movement by modulating their motions through a reduced set of few principal patterns. Finally, we discuss how this approach could be profitably applied in robotics and bioengineering, opening fascinating perspectives to advance the state of the art of artificial systems, as it was the case of hand synergies.

}, author = {G. Averta and C. Della Santina and E. Battaglia and F. Felici and M. Bianchi and A. Bicchi} }