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Elenco Pubblicazioni - Publications (1288)

Mura, D., Knoop, E., Catalano, M. G., Grioli, G., Bächer, M., & Bicchi, A. (2020). On the role of stiffness and synchronization in human–robot handshaking. The International Journal of Robotics Research.

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This article presents a system for soft human–robot handshaking, using a soft robot hand in conjunction with a lightweight and impedance-controlled robot arm. Using this system, we study how different factors influence the perceived naturalness,…
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L. Fiaschi, M. Cococcioni. Numerical Asymptotic Results in Game Theory Using Sergeyev’s Infinity Computing, International Journal of Unconventional Computing (IJUC), pp. 1-25(1) 2018.

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ABSTRACT  Prisoner's Dilemma (PD) is a widely studied game that plays an important role in Game Theory. This paper aims at extending PD Tournaments to the case of infinite, finite or infinitesimal payoffs using Sergeyev's…
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L. Fiaschi, M. Cococcioni. Generalizing Pure and Impure Iterated Prisoner's Dilemmas to the Case of Infinite and Infinitesimal Quantities, In Numerical Computations: Theory and Algorithms, pages 370–377, Cham, 2020. Springer Intern. Publishing

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ABSTRACT In this work we aim at generalizing Pure and Impure PD iterated games when using finite/infinite/infinitesimal payoffs and finite/infinitesimal probabilities, i.e., dealing with non-Archimedean quantities (realm so far investigated only on the theoretical side).…
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M. Cococcioni, F. Rossi, E. Ruffaldi, and S. Saponara. "A fast approximation of the hyperbolic tangent when using posit numbers and its application to deep neural networks", (ApplePies’19), 2019.

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Deep Neural Networks (DNNs) are being used in more and more fields. Among the others, automotive is a field where deep neural networks are being exploited the most. An important aspect to be considered is…
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M. Cococcioni, F. Rossi, E. Ruffaldi, and S. Saponara. "Novel arithmetics to accelerate machine learning classifiers in autonomous driving applications", 26th IEEE International Conference on Electronics Circuits and Systems(ICECS’19), 2019.

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Autonomous driving techniques frequently need the clustering and the classification of data coming from several input sensors, like cameras, radar and lidars. These sub-tasks need to be implemented in real-time in embedded on-board computing units.…
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