Publications

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Authors: eng 2-s2.0-14044265713

Journal: Italy||Italy||Italy

Published: doi

DOI: University of Padua||University of Padua||Institute ISIB of CNR Padua

Volume: Menegatti E.; Pretto A.; Pagello E. Pages: Menegatti||Pretto||Pagello-One of the most challenging issue in mobile robot navigation is the localization problem in densely populated environments. In this paper, we present a new approach for vision-based localization able to solve this problem. The omnidirectional camera is used as a range finder sensitive to the distance of color transitions, whereas classical range finders, like lasers or sonars, are sensitive to the distance of the nearest obstacles. The well-known Monte-Carlo localization technique was adapted for this new type of range sensor. The system runs in real time on a low-cost pc. In this paper we present experiments, performed in a crowded RoboCup Middle-size field, proving the robustness of the approach to the occlusions of the vision sensor by moving obstacles (e.g other robots); occlusions that are very likely to occur in a real environment. Although, the system was implemented for the RoboCup environment, the system can be used in more general environments.

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Authors: 14 HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY; eng 2-s2.0-84943232643

Journal: Italy||Italy||Italy||Italy||Italy||Italy||Italy||Italy||Italy||Italy

Published: false

DOI: University of Padua||University of Padua||University of Padua||University of Padua||University of Padua||University of Padua||University of Padua||University of Padua||University of Padua||University of Padua

Volume: Pagello E.; Menegatti E.; Bredenfeld A.; Costa P.; Christaller T.; Jacoff A.; Johnson J.; Riedmiller M.; Saffiotti A.; Tomoichi T. Pages: Pagello||Menegatti||Bredenfeld||Costa||Christaller||Jacoff||Johnson||Riedmiller||Saffiotti||Tomoichi

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Authors: 98 445 BURGESS DRIVE, MENLO PK, CA 94025-3496 USA; eng 2-s2.0-3142721990

Journal: Italy||Italy||Germany||Portugal||United States||Germany||Germany||Sweden||United States||Japan

Published: 25

DOI: Dept. of Information Eng.||University of Padua||Fraunhofer Inst. for Autonomous||Porto University||NIST||Univ. of Mainz's Fac. of Math.||Univ. of Karlsruhe||University of Orebro||Columbia Univ.||Nagoya University

Volume: Pagello E.; Menegatti E.; Bredenfel A.; Costa P.; Christaller T.; Jacoff A.; Polani D.; Riedmiller M.; Saffiotti A.; Sklar E.; Tomoichi T. Pages: Pagello||Menegatti||Bredenfel||Costa||Christaller||Jacoff||Polani||Riedmiller||Saffiotti||Sklar||Tomoichi-This article reports on the RoboCup-2003 event. RoboCup is no longer just the Soccer World Cup for autonomous robots but has evolved to become a coordinated initiative encompassing four different robotics events: (1) Soccer, (2) Rescue, (3) Junior (focused on education), and (4) a Scientific Symposium. RoboCup-2003 took place from 2 to 11 July 2003 in Padua (Italy); it was colocated with other scientific events in the field of AI and robotics. In this article, in addition to reporting on the results of the games, we highlight the robotics and AI technologies exploited by the teams in the different leagues and describe the most meaningful scientific contributions. © 2004, American Association for Artificial Intelligence. All rights reserved.

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Authors: eng 2-s2.0-14044250905

Journal: Italy||Italy||Italy||Italy||Japan

Published: doi

DOI: University of Padua||National Council of Research||University of Padua||National Council of Research||Osaka University

Volume: Menegatti E.; Cicirelli G.; Simionato C.; D'Orazio T.; Ishiguro H. Pages: Menegatti||Cicirelli||Simionato||D'Orazio||Ishiguro-This paper presents an Omnidirectional Distributed Vision System that learns to navigate a robot in an office-like environment without any knowledge about the calibration of the cameras or the robot control law. The system is composed of several omnidirectional Vision Agents (implemented with an omnidirectional camera and a computer). The first Vision Agent learns to control the robot with SARSA(λ) reinforcement learning, using the LEM strategy to speed-up learning. Once the first Vision Agent learnt the correct policy, it transfers its knowledge to the other Vision Agents. The other Vision Agents might have different intrinsic and extrinsic camera parameters (that are unknown), so a certain amount of re-learning is needed. Reinforcement learning is well suited for this. In this paper, we present the structure of the learning system and the discussion about the optimal values for the learning parameters. During the experimentation the learning phase of the first agent has been carried out, then the knowledge propagation and the re-learning stage of three different agents have been tested. The experimental results demonstrate the feasibility of the approach and the possibility to port the system on the actual robot and cameras.

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Authors: AREA MIN. 09 - Ingegneria industriale e dell'informazione; Non assegn; ITA; 2015-06-05T03:19:24Z; 9781586034146

Published: MATCH_RESULT_STATUS_FAILURE_NO_MATCH

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Authors: 283 125 London Wall, London, ENGLAND; eng 2-s2.0-0347915529

Journal: Italy||Italy||Italy||Italy||Italy||Italy||Italy||Italy

Published: Elsevier Ltd

DOI: University of Padova||University of Ferrara||University of Ferrara||University of Ferrara||University of Ferrara||University of Ferrara||University of Ferrara||University of Ferrara

Volume: Altavilla G.; Caputo A.; Trabanelli C.; Brocca Cofano E.; Sabbioni S.; Menegatti M.A.; Barbanti-Brodano G.; Corallini A. Pages: Altavilla||Caputo||Trabanelli||Brocca Cofano||Sabbioni||Menegatti||Barbanti-Brodano||Corallini-The human immunodeficiency virus type 1 (HIV-1) Tat protein stimulates cell proliferation, inhibits apoptosis, displays angiogenic functions and is believed to be involved in the pathogenesis of Kaposi's sarcoma (KS) and other tumours arising in AIDS patients. Tat-transgenic (TT) mice, which constitutively express Tat in all tissues and organs, may therefore be predisposed to tumorigenesis. To test this hypothesis, we treated TT mice with urethane, a general carcinogen inducing tumours of various organs. The results indicate that, after injection of urethane, the incidence of lung tumours and lymphomas is not significantly different in the TT and control (CC) mice, whereas liver preneoplastic lesions and tumours show a significantly greater incidence in TT than in CC mice. This remarkable carcinogenic effect of urethane for the liver may be due to a tat-induced predisposition, manifested as a liver cell dysplasia (LCD), spontaneously affecting most of the TT mice. LCD may exert a promoting effect by stimulating proliferation of cell clones initiated by the mutagenic effect of urethane. In addition, LCD, which is associated with aneuploidy and chromosome instability, may enhance the progression to malignancy of the preneoplastic lesions induced by urethane. Interestingly, a significantly greater incidence of vascular ectasias and haemangiomas was detected in the liver of urethane-treated TT mice, most likely due to the marked angiogenic properties of Tat. This study suggests a role for Tat in the promotion and progression of tumours initiated by exogenous and endogenous carcinogens in HIV-1-infected patients, thereby contributing to the tumorigenesis in the course of AIDS. © 2003 Elsevier Ltd. All rights reserved.

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Authors: AREA MIN. 09 - Ingegneria industriale e dell'informazione; Non assegn; 2015-06-05T04:36:32Z

Published: MATCH_RESULT_STATUS_FAILURE_NO_MATCH

W36965723

Authors: AREA MIN. 09 - Ingegneria industriale e dell'informazione; Non assegn; ITA; 2015-06-05T04:37:08Z; 9781586034146

Published: title_year

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Authors: AREA MIN. 09 - Ingegneria industriale e dell'informazione; Non assegn; ITA; 2015-06-05T03:44:34Z; 9788889422090

Published: MATCH_RESULT_STATUS_FAILURE_NO_MATCH

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Authors: 30 RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS; eng 2-s2.0-3342937744

Journal: Italy||Italy||Italy||Japan

Published: false

DOI: University of Padua||University of Padua||CNR||Osaka University

Volume: Menegatti E.; Zoccarato M.; Pagello E.; Ishiguro H. Pages: Menegatti||Zoccarato||Pagello||Ishiguro-Monte Carlo localisation generally requires a metrical map of the environment to calculate a robots position from the posterior probability density of a set of weighted samples. Image-based localisation, which matches a robots current view of the environment with reference views, fails in environments with perceptual aliasing. The method we present in this paper is experimentally demonstrated to overcome these disadvantages in a large indoor environment by combining Monte Carlo and image-based localisation. It exploits the properties of the Fourier transform of omnidirectional images, while weighting the samples according to the similarity among images. We also introduce a novel strategy for solving the "kidnapped robot problem". © 2004 Elsevier B.V. All rights reserved.