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Novedrate, Italy

Palpacelli M.,Marche Polytechnic University | Carbonari L.,Marche Polytechnic University | Palmieri G.,ampus University
MESA 2014 - 10th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, Conference Proceedings | Year: 2014

The paper proposes the mechanical design of a lockable spherical joint, which is designed to be manually or automatically configured in different kinematic solutions. In fact it can be used as a conventional spherical joint or converted in a universal joint or still downgraded to a revolute joint. Therefore different configurations can be chosen according to user needs. In particular, two of the three axes of revolution, arranged in the typical roll-pitch-roll sequence of robot spherical wrists, can be locked alternatively in order to provide two differently arranged U-joints. It can be demonstrated that such behavior allows to activate different mobilities of two classes of reconfigurable parallel kinematics manipulators. The transition between such mobilities occurs exploiting the concept of over-constrained kinematics, which is realized by the lockable joint during the switching phase in order to avoid an instantaneous mobility of the robot. © 2014 IEEE.

Padulo J.,ampus University | Padulo J.,SPO Sport Performance Optimization Laboratory | Pizzolato F.,University of Verona | Tosi Rodrigues S.,Sao Paulo State University | And 6 more authors.
Journal of Sports Medicine and Physical Fitness | Year: 2016

BACKGROUND: The purpose of this study was to examine the effect of intensive practice in table tennis on perceptual, decision-making and motor-systems. Groups of elite (HL, N.=11), intermediate (LL, N.=6) and control players (CC, N.=11) performed tasks of different levels. METHODS: All subjects underwent to reaction time test and response time test consisting of a pointing task to targets placed at distinct distances (15 and 25 cm away) on the right and left sides. Only the HL and LL groups were requested to perform the ball speed test in forehand and backhand condition. RESULTS: In the CC group reaction time was higher compared to the HL (P<0.05) group. In the response time test, there was a significant main effect of distance (P<0.0001) and the tennis table expertise (P=0.011). In the ball speed test HL players were consistently faster compared to LL players in both forehand stroke (P<0.0001) and backhand stroke (P<0.0001). Overall, the forehand stroke was significantly faster than the backhand stroke. CONCLUSIONS: We can conclude that table tennis players have shorter response times than non-athletes and the tasks of reaction time and response time are incapable to distinguish between the performance of well-trained table tennis players and that of intermediate players, but the ball speed test seems to be able to do it. © 2016 EDIZIONI MINERVA MEDICA.

Battilotti S.,University of Rome La Sapienza | Delli Priscoli F.,University of Rome La Sapienza | Gori Giorgi C.,University of Rome La Sapienza | Monaco S.,University of Rome La Sapienza | And 4 more authors.
Chinese Control Conference, CCC | Year: 2015

In the perspective of the emerging Future Internet framework, the Quality of Experience (QoE) Control functionalities are aimed at approaching the desired QoE level of the applications by dynamically selecting the most appropriate Classes of Service supported by the network. In the present work, this selection is driven by Multi-Agent Reinforcement Learning, namely by the Friend-Q learning algorithm. The proposed dynamic approach differs from the traffic classification approaches found in the literature, where a static assignment of Classes of Service to application instances is performed. All these improvements are aimed at adding a cognition loop to telecommunication networks, by making use of Multi-Agent Reinforcement Learning, and at fostering the intelligent connectivity between applications and networks. © 2015 Technical Committee on Control Theory, Chinese Association of Automation.

Palpacelli M.,Marche Polytechnic University | Palmieri G.,ampus University | Carbonari L.,Marche Polytechnic University | Callegari M.,Marche Polytechnic University
Advanced Robotics | Year: 2014

The present paper addresses the modelling and the experimental identification of the static behaviour of the Tricept robot, a hybrid parallel kinematic machine. Mass properties of robot links are initially hypothesized from solid modelling and then incorporated in the identification procedure. Coulomb friction and gravity contributions to motor torques are taken into account: their identification is carried out by means of ordinary least-squares algorithms based on motor currents measurements during several slow motion tests. Moreover, the effect of external forces applied at the end-effector is introduced in the model and analysed by driving the robot end-effector against a calibrated compliant cell. Eventually, the static model is profitably used in an industrial operation of Friction Stir Welding to estimate the external forces applied at the tool mechanical interface providing some benefits: a deeper understanding of the technological process parameters and the possibility to realize model-based controls. © 2014 Taylor & Francis and The Robotics Society of Japan.

D'Andrea E.,University of Pisa | Ducange P.,ampus University | Lazzerini B.,University of Pisa | Marcelloni F.,University of Pisa
IEEE Transactions on Intelligent Transportation Systems | Year: 2015

Social networks have been recently employed as a source of information for event detection, with particular reference to road traffic congestion and car accidents. In this paper, we present a real-time monitoring system for traffic event detection from Twitter stream analysis. The system fetches tweets from Twitter according to several search criteria; processes tweets, by applying text mining techniques; and finally performs the classification of tweets. The aim is to assign the appropriate class label to each tweet, as related to a traffic event or not. The traffic detection system was employed for real-time monitoring of several areas of the Italian road network, allowing for detection of traffic events almost in real time, often before online traffic news web sites. We employed the support vector machine as a classification model, and we achieved an accuracy value of 95.75% by solving a binary classification problem (traffic versus nontraffic tweets). We were also able to discriminate if traffic is caused by an external event or not, by solving a multiclass classification problem and obtaining an accuracy value of 88.89%. © 2000-2011 IEEE.

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