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Institution

Istituto Italiano di Tecnologia

FacilityGenoa, Italy
About: Istituto Italiano di Tecnologia is a facility organization based out in Genoa, Italy. It is known for research contribution in the topics: Robot & Humanoid robot. The organization has 4561 authors who have published 14595 publications receiving 437558 citations. The organization is also known as: Italian Institute of Technology & IIT.
Topics: Robot, Humanoid robot, Graphene, iCub, Nanoparticle


Papers
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Journal ArticleDOI
TL;DR: This paper develops a framework that enables the robot to learn both movement and stiffness features from the human tutor and can be efficiently realized by the proposed framework.
Abstract: One promising approach for robots efficiently learning skills is to learn manipulation skills from human tutors by demonstration and then generalize these learned skills to complete new tasks. Traditional learning and generalization methods, however, have not well considered human impedance features, which makes the skills less humanlike and restricted in physical human–robot interaction scenarios. In particular, stiffness generalization has not been well considered. This paper develops a framework that enables the robot to learn both movement and stiffness features from the human tutor. To this end, the upper limb muscle activities of the human tutor are monitored to extract variable stiffness in real time, and the estimated human arm endpoint stiffness is properly mapped into the robot impedance controller. Then, a dynamic movement primitives model is extended and employed to simultaneously encode the movement trajectories and the stiffness profiles. In this way, both position trajectory and stiffness profile are considered for robot motion control in this paper to realize a more complete skill transfer process. More importantly, stiffness generalization and movement generalization can be efficiently realized by the proposed framework. Experimental tests have been performed on a dual-arm Baxter robot to verify the effectiveness of the proposed method.

150 citations

Journal ArticleDOI
TL;DR: Findings indicate that some small activators of Nrf2/HO-1 are effective modulators of microglia inflammation and highlight the chemical scaffolds that can serve for the synthesis of potent new derivatives to counteract neuroinflammation and neurodegeneration.

150 citations

Journal ArticleDOI
TL;DR: A bottom-up approach for the realization of bioactive scaffolds with controllable pore size and interconnection, combined with protein-loaded polymeric microcarriers acting as local chrono-programmed point source generation of bio active signals is proposed.

150 citations

Journal ArticleDOI
TL;DR: This model shows that available knowledge on cellular mechanisms is sufficient to unify the main functional hypotheses on the cerebellum granular layer and suggests that this network can behave as an adaptable spatio-temporal filter coordinated by theta-frequency oscillations.
Abstract: The way the cerebellar granular layer transforms incoming mossy fiber signals into new spike patterns to be related to Purkinje cells is not yet clear. Here, a realistic computational model of the granular layer was developed and used to address four main functional hypotheses: center-surround organization, time-windowing, high-pass filtering in responses to spike bursts and coherent oscillations in response to diffuse random activity. The model network was activated using patterns inspired by those recorded in vivo. Burst stimulation of a small mossy fiber bundle resulted in granule cell bursts delimited in time (time windowing) and space (center-surround) by network inhibition. This burst-burst transmission showed marked frequency-dependence configuring a high-pass filter with cut-off frequency around 100 Hz. The contrast between center and surround properties was regulated by the excitatory-inhibitory balance. The stronger excitation made the center more responsive to 10-50 Hz input frequencies and enhanced the granule cell output (with spike occurring earlier and with higher frequency and number) compared to the surround. Finally, over a certain level of mossy fiber background activity, the circuit generated coherent oscillations in the theta-frequency band. All these processes were fine-tuned by NMDA and GABA-A receptor activation and neurotransmitter vesicle cycling in the cerebellar glomeruli. This model shows that available knowledge on cellular mechanisms is sufficient to unify the main functional hypotheses on the cerebellum granular layer and suggests that this network can behave as an adaptable spatio-temporal filter coordinated by theta-frequency oscillations.

149 citations

Journal ArticleDOI
TL;DR: It is shown that a suspended red blood cell behaves as an adaptive liquid-lens at microscale, thus demonstrating its imaging capability and tunable focal length and blood diagnosis is demonstrated by screening abnormal cells through focal-spot analysis applied to an RBC ensemble as a microlens array.
Abstract: The perspective of using live cells as lenses could open new revolutionary and intriguing scenarios in the future of biophotonics and biomedical sciences for endoscopic vision, local laser treatments via optical fibres and diagnostics. Here we show that a suspended red blood cell (RBC) behaves as an adaptive liquid-lens at microscale, thus demonstrating its imaging capability and tunable focal length. In fact, thanks to the intrinsic elastic properties, the RBC can swell up from disk volume of 90 fl up to a sphere reaching 150 fl, varying focal length from negative to positive values. These live optofluidic lenses can be fully controlled by triggering the liquid buffer's chemistry. Real-time accurate measurement of tunable focus capability of RBCs is reported through dynamic wavefront characterization, showing agreement with numerical modelling. Moreover, in analogy to adaptive optics testing, blood diagnosis is demonstrated by screening abnormal cells through focal-spot analysis applied to an RBC ensemble as a microlens array.

149 citations


Authors

Showing all 4601 results

NameH-indexPapersCitations
Marc G. Caron17367499802
Paolo Vineis134108886608
Michele Parrinello13363794674
Alex J. Barker132127384746
Tomaso Poggio13260888676
Shuai Liu129109580823
Giacomo Rizzolatti11729897242
Yehezkel Ben-Ari11045944293
Daniele Piomelli10450549009
Bruno Scrosati10358066572
Wolfgang J. Parak10246943307
Liberato Manna9849444780
Muhammad Imran94305351728
Ole Isacson9334530460
Luigi Ambrosio9376139688
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202313
2022109
20211,576
20201,618
20191,439
20181,381