Ricerca, la scienza con i videogiochi. Simulazioni interattive per il laboratorio – Repubblica.it.

Sergey Brin: Why Google Glass? | Video on TED.com.

Intel International Science and Engineering Fair.

Google X’s Sebastian Thrun on How To Invent Amazing Products.

Google Launches “Hangouts” Messaging Service for iOS, Android, and Web.

Wearable devices expected to be a $6 billion ecosystem in just 3 years.

Sole 24 ore_13/05

Robotic hands differ in kinematics, dynamics, programming, control and sensing frameworks. Their common character is redundancy, which undoubtedly represents a key feature for dexterity and flexibility, but it is also a drawback for integrated automation since it typically requires additional efforts to seamlessly integrate devices, particularly robotic hands, in industrial scenario. This research focuses on the mapping between hands with dissimilar kinematics. It is based on the argument that the reflected optimality of the pattern of grasping forces emerging from human hand synergies should be matched, in some sense, by the sought for postural synergies of robotic hands. As a natural consequence of the proposed approach, postural synergies for different kinematic structures could look entirely different in geometric shape. This difference should be a consequence of aspects such as different dimensions, kinematic structures, number of fingers, compliance, contact properties which cannot come into play if a gross geometric mapping is applied. The proposed mapping is based on the use of a virtual sphere and will be mediated by a model of an anthropomorphic robotic hand able to capture the idea of synergies in human hands. The main advantage of this approach is that the high level control (human synergies) is substantially independent from the robotic hand and depends only on the specific operation to be performed. It could then be possible, for example, to use the same controller with different robotic hands, or simply substitute a device without changing the controller, thus realizing a sort of abstraction layer for robotic hand control based on postural synergies.

References

G. Gioioso, G. Salvietti, M. Malvezzi, D. Prattichizzo. Mapping Synergies from Human to Robotic Hands with Dissimilar Kinematics: an Approach in the Object Domain. IEEE Trans. on Robotics, In press, 2013.

G. Gioioso, G. Salvietti, M. Malvezzi, D. Prattichizzo. An Object-Based Approach to Map Human Hand Synergies onto Robotic Hands with Dissimilar Kinematics. In Robotics: Science and Systems VIII, The MIT Press, Sidney, Australia, July 2012.

G. Gioioso, G. Salvietti, M. Malvezzi and P. Prattichizzo “Mapping synergies from human to robotic hands with dissimilar kinematics: an object based approach”, in Proc. of Workshop “Manipulation Under Uncertainty” International Conference on Robotics an Automation, ICRA 2011

Video

This video shows an application of the mapping algorithm in the EU funded experiment HANDS.DVI in the context of the ECHORD project.

In this video it is shown how the object-based mapping can be easily implemented in our Matlab Toolbox Syngrasp

    Incontro con il Dr. Massimo Vita, Vice Presidente e Consigliere sezionale dell’ Unione Italiana Ciechi ed Ipovedenti a Siena.

I Completely Disconnected for 10 Days. Here\’s What Happened.