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Alamanni, Italy

Colla V.,Polytechnic University of Turin | Vannucci M.,TeCIP Institute | Reyneri L.M.,Polytechnic University of Turin
Intelligent Data Analysis | Year: 2014

The estimate of the probability density function or probability mass function of an unknown stochastic process is a very important preliminary step for any further elaboration. Most of the traditional approaches to this problem perform a preliminary choice of a parametric mathematical model of the function to estimate and a subsequent fitting on its parameters. To this aim some a-priori knowledge and/or assumptions on the phenomenon under consideration are needed. In this paper an alternative approach is proposed, which does not require any assumption on the available data, as it extracts the probability density function from the output of a neural network, that is trained with a suitable database including the original data and some ad hoc created data with known distribution. The results of the tests performed on synthetic and industrial databases are described and discussed in the paper. © 2015 - IOS Press and the authors. All rights reserved. Source


Rosati Papini G.P.,TeCIP Institute | Avizzano C.A.,TeCIP Institute
Proceedings - IEEE International Workshop on Robot and Human Interactive Communication | Year: 2012

The Body Extender is a whole-body exoskeleton designed to operate in unknown and difficult environments, for instance in disaster areas. The Body Extender allows the wearing operator to increase its force while maintaining a high level of perception. © 2012 IEEE. Source


Di Fava A.,SantAnna School of Advanced Studies | Satler M.,TeCIP Institute | Tripicchio P.,TeCIP Institute
2015 23rd Mediterranean Conference on Control and Automation, MED 2015 - Conference Proceedings | Year: 2015

In many applications, robots should be able to move autonomously in semi-structured or unstructured environments. Autonomous robots can be employed for instance in area patrolling tasks in order to perform surveillance of sites. To autonomously navigate in an unknown outdoor scenario, a robot should be able to acquire sensible information about the environment by means of its own sensors and at the same time perform some reasoning to decide where and how to move. In this paper, we present a vision-based solution for the decision making and a behavior based low-level control for the navigation. Three different testing scenarios have been employed to assess the capabilities of the proposed approach: a computer simulated scenario, an indoor test on a real robotic platform and finally an outdoor test in a city park. © 2015 IEEE. Source


Moretti G.,TeCIP Institute | Rosati G.P.P.,TeCIP Institute | Fontana M.,TeCIP Institute | Vertechy R.,University of Bologna
MTS/IEEE OCEANS 2015 - Genova: Discovering Sustainable Ocean Energy for a New World | Year: 2015

This paper presents a small-scale test-bench that can be employed for the study of a new class of Oscillating Water Column (OWC) Wave Energy Converters (WECs) with Power Take Off (PTO) unit based on Dielectric Elastomer Generators (DEGs). Such a test-bench is designed to perform Hardware-In-the-Loop (HIL) simulations of a small-scale DEG PTO prototype, that includes dedicated power and control electronics, with a real-time model that emulates OWC plant hydrodynamics. The paper illustrates the theoretical model that is assumed to describe the dynamics of the OWC plant, the hardware employed to replicate the response of the DEG PTO and the algorithms for the implementation of the closed-loop controller that performs the HIL simulations. Some preliminary tests are reported considering a floating OWC collector and a simple energy-harvesting control law for the DEG PTO that is based on the measurement of the water level into the OWC structure. © 2015 IEEE. Source


Leonardis D.,TeCIP Institute | Frisoli A.,TeCIP Institute | Barsotti M.,TeCIP Institute | Vanello N.,University of Pisa | Bergamasco M.,TeCIP Institute
Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics | Year: 2012

Motor imagery techniques are largely used in asynchronous BCI for the control of external devices. In this work we comparatively evaluate the performance of different state-of arts BCI algorithms, based on the Common Spatial Pattern approach, under different sensory feedback conditions. In particular the role of tendon vibration, inducing illusory movement, is analyzed in the context of BCI for motor imagery. © 2012 IEEE. Source

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