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16th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2016

作者： Ćesić, Josip Joukov, Vladimir Petrović, Ivan Kulić, Dana University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Autonomous Systems and Mobile Robotics Croatia University of Waterloo Department of Electrical and Computer Engineering Adaptive Systems Laboratory Canada

ISBN: (纸本)9781509047185

This paper proposes a new algorithm for full body human motion estimation using 3D marker position measurements. The joints are represented with Lie group members, including special orthogonal groups SO(2) and SO(3), and a special euclidean group SE(3). We employ the Lie Group Extended Kalman Filter (LG-EKF) for stochastic inference on groups, thus explicitly accounting for the non-euclidean geometry of the state space, and provide the derivation of the LG-EKF recursion for articulated motion estimation. We evaluate the performance of the proposed algorithm in both simulation and on real-world motion capture data, comparing it with the Euler angles based EKF. The results show that the proposed filter significantly outperforms the Euler angles based EKF, since it estimates human motion more accurately and is not affected by gimbal lock. © 2016 IEEE.

关键词： Extended Kalman filters

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Shape-independent hardness estimation using deep learning and a GelSight tactile sensor

Shape-independent hardness estimation using deep learning an...

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2017 IEEE International Conference on robotics and Automation, ICRA 2017

作者： Yuan, Wenzhen Zhu, Chenzhuo Owens, Andrew Srinivasan, Mandayam A. Adelson, Edward H. MIT CambridgeMA02139 United States CSAIL MIT CambridgeMA United States Electrical Engineering and Computer Science Department U.C. Berkeley and CSAIL MIT CambridgeMA02139 United States Research Laboratory of Electronics Department of Mechanical Engineering MIT CambridgeMA02139 United States Department of Brain and Cognitive Sciences CSAIL MIT CambridgeMA02139 United States

ISBN: (纸本)9781509046331

Hardness is among the most important attributes of an object that humans learn about through touch. However, approaches for robots to estimate hardness are limited, due to the lack of information provided by current tactile sensors. In this work, we address these limitations by introducing a novel method for hardness estimation, based on the GelSight tactile sensor, and the method does not require accurate control of contact conditions or the shape of objects. A GelSight has a soft contact interface, and provides high resolution tactile images of contact geometry, as well as contact force and slip conditions. In this paper, we try to use the sensor to measure hardness of objects with multiple shapes, under a loosely controlled contact condition. The contact is made manually or by a robot hand, while the force and trajectory are unknown and uneven. We analyze the data using a deep constitutional (and recurrent) neural network. Experiments show that the neural net model can estimate the hardness of objects with different shapes and hardness ranging from 8 to 87 in Shore 00 scale. © 2017 IEEE.

关键词： Hardness

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Shape-independent hardness estimation using deep learning and a GelSight tactile sensor

Shape-independent hardness estimation using deep learning an...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Wenzhen Yuan Chenzhuo Zhu Andrew Owens Mandayam A. Srinivasan Edward H. Adelson Department of Mechanical Engineering Computer Science and Artificial Intelligence Laboratory (CSAIL) Cambridge MA USA CSAIL MIT Cambridge MA USA Department of Electronical Engineering Tsinghua University Beijing China Electrical Engineering and Computer Science Department MIT Cambridge MA USA Computer Science Department UCL TouchLab London UK Department of Mechanical Engineering Research Laboratory of Electronics Cambridge MA USA Department of Brain and Cognitive Sciences and CSAIL MIT Cambridge MA USA

关键词： Force Tactile sensors Force measurement Shape Geometry

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BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series

引用

Global Ecology and Biogeography 2025年第5期34卷

作者： Maria Dornelas Laura H. Antão Amanda E. Bates Viviana Brambilla Jonathan M. Chase Cher F. Y. Chow Ada Fontrodona-Eslava Anne E. Magurran Inês S. Martins Faye Moyes Alban Sagouis Samuel Adu-Acheampong Daniel Acquah-Lamptey Dušan Adam Penelope A. Ajani Aitor Albaina Pablo Almaraz Jeongseop An Roger Sigismund Anderson Madelaine Jean Robertson Anderson Alexsander Z. Antunes Ivan Arismendi Linda Armbrecht Pedro Aros-Mardones Sreejith Kalpuzha Ashtamoorthy Narayanan Ayyappan Gal Badihi Joseph J. Bailey Andrew H. Baird Mark Edward Baird Sreekumar Vadakkethil Balakrishnan José António L. Barão-Nóbrega Adi Barash Miguel Barbosa Jos Barlow Claus Bässler Matthieu Beaumont Natalie Beenaerts Tiago Octavio Begot Wallace Beiroz Ricardo Beldade David M. Bell Alecia Bellgrove Jonathan Belmaker Lisandro Benedetti-Cecchi Cassandra E. Benkwitt Pamela Medina-van Berkum Brandon T. Bestelmeyer Matthew G. Betts Maxwell Kelvin Billah Anne D. Bjorkman Magdalena Błażewicz Christopher P. Bloch Shane A. Blowes Antonio Bode Juliano A. Bogoni Thomas Bolger Timothy C. Bonebrake Erik Bonsdorff Roberta Bottarin Luke N. Brokensha Rob W. Brooker Andrew J. Brooks Helge Bruelheide Thiago Almeida Bueno Claire Laguionie Mariana Lopes Campagnoli James Cant Erica Pellegrini Caramaschi Alexandre Caron Tadhg Carroll Tancredi Caruso Juan Carvajal-Quintero Giuseppe Castaldelli Edward Castañeda-Moya Pedro V. Castilho Sonia Zanini Cechin Shahar Chaikin Uchangi Manjunatha Chandrashekara Tory J. Chase Chaolun Allen Chen Jorge José Cherem Sei-Woong Choi Erica M. Christensen Alexander V. Christianini Jackson Wing Four Chu Peter Coad Carl Van Colen Lise Comte Elisabeth J. Cooper J. Hans C. Cornelissen Eddy Cosson Unai Cotano Luc Crevecoeur Shannan Kyle Crow Graeme S. Cumming Vanessa S. Daga Gabriella Damasceno Gergana N. Daskalova Claire H. Davies Robert A. Davis Frank P. Day Sussy De-La-Zerda Amy Elizabeth Deacon Indradatta de Castro-Arrazola Steven Degraer Kharran Deonarinesingh Juan C. Diaz-Ricaurte Christopher R. Dickman Tara Dirilgen Ciaran John Dolan J. Emmet Centre for Biological Diversity School of Biology University of St Andrews Fife UK MARE—Centro de Ciências do Mar e do Ambiente Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Research Centre for Ecological Change Organismal and Evolutionary Biology Research Programme Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland Department of Biology University of Victoria Victoria British Columbia Canada German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig Leipzig Germany Department of Computer Science Martin Luther University Halle-Wittenberg Halle (Saale) Germany Leverhulme Centre for Anthropocene Biodiversity Department of Biology University of York York UK Department of Animal Biology and Conservation Science University of Ghana Accra Ghana Philipps Universität Marburg Marburg Germany Department of Forest Ecology Silva Tarouca Research Institute Brno Czech Republic School of Life Sciences University of Technology Sydney Sydney New South Wales Australia Zoology and Animal Cell Biology Department University of the Basque Country (UPV/EHU) Leioa Spain Grupo de Oceanografía de Ecosistemas Instituto de Ciencias Marinas de Andalucía CSIC Campus Universitario de Puerto Real Puerto Real Spain National Institute of Ecology Seocheon Republic of Korea African Regional Postgraduate Programme in Insect Science University of Ghana Accra Ghana Département de Biologie Université de Sherbrooke Sherbrooke Quebec Canada Núcleo de Conservação da Biodiversidade Instituto de Pesquisas Ambientais Secretaria de Meio Ambiente Infraestrutura e Logística do Estado de São Paulo São Paulo Brazil Department of Fisheries Wildlife and Conservation Sciences Oregon State University Corvallis Oregon USA Institute for Marine and Antarctic Studies Ecology & Biodiversity Centre University of Tasmania Hobart Tasmania Australia Graduate Program in Oceanography Department of Oceanography Faculty of Natural Scienc

Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

关键词： assemblage biodiversity community database ecoinformatics species taxa time

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The ultra-high-energy event KM3-230213A within the global neutrino landscape

arXiv

引用

arXiv 2025年

作者： Adriani, O. Aiello, S. Albert, A. Alhebsi, A.R. Alshamsi, M. Garre, S. Alves Ambrosone, A. Ameli, F. Andre, M. Aphecetche, L. Ardid, M. Ardid, S. Argüelles, C. Aublin, J. Badaracco, F. Bailly-Salins, L. Bardačová, Z. Baret, B. Bariego-Quintana, A. Becherini, Y. Bendahman, M. Gualandi, F. Benfenati Benhassi, M. Bennani, M. Benoit, D.M. Berbee, E. Berti, E. Bertin, V. Betti, P. Biagi, S. Boettcher, M. Bonanno, D. Bottai, S. Bouasla, A.B. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzaş, H. Bretaudeau, F. Breuhaus, M. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Clark, R. Cocimano, R. Coelho, J.A.B. Coleiro, A. Condorelli, A. Coniglione, R. Coyle, P. Creusot, A. Cuttone, G. Dallier, R. De Benedittis, A. De Wasseige, G. Decoene, V. Deguire, P. Del Rosso, I. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Drakopoulou, E. Drouhin, D. Ducoin, J.-G. Duverne, P. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. El Mentawi, S. Ellajosyula, V. Enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gal, T. Méndez, J. García Soto, A. Garcia Oliver, C. Gatius Geißelbrecht, N. Genton, E. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Goos, I. Goswami, P. Gozzini, S.R. Gracia, R. Guidi, C. Guillon, B. Gutiérrez, M. Haack, C. van Haren, H. Heijboer, A. Hennig, L. Hernández-Rey, J.J. Idrissi, A. Ibnsalih, W. Idrissi Illuminati, G. Janik, O. Joly, D. de Jong, M. de Jong, P. Jung, B.J. Kalaczyński, P. Kamp, N. Keegans, J. Kikvadze, V. Kistauri, G. Kopper, C. Kouchner, A. Kovalev, Y.Y. Krupa, L. Kueviakoe, V. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. INFN Sezione di Firenze via Sansone 1 Sesto Fiorentino50019 Italy Università di Firenze Dipartimento di Fisica e Astronomia via Sansone 1 Sesto Fiorentino50019 Italy Via Santa Sofia 64 Catania95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France Université de Haute Alsace rue des Frères Lumière Mulhouse68093 Cedex France Khalifa University of Science and Technology Department of Physics PO Box 127788 Abu Dhabi United Arab Emirates Aix Marseille Univ CNRS IN2P3 CPPM Marseille France c/Catedrático José Beltrán 2 Valencia Paterna46980 Spain Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain Subatech IMT Atlantique IN2P3-CNRS Nantes Université 4 rue Alfred Kastler - La Chantrerie BP Nantes20722 44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia46730 Spain Harvard University Department of Physics Laboratory for Particle Physics and Cosmology Lyman Laboratory 17 Oxford St. CambridgeMA02138 United States Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France INFN Sezione di Genova Via Dodecaneso 33 Genova16146 Italy Università di Genova Via Dodecaneso 33 Genova16146 Italy LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen14050 France Comenius University in Bratislava Department of Nuclear Physics and Biophysics Mlynska dolina F1 Bratislava842 48 Slovakia Czech Technical University in Prague Institute of Experimen

On February 13th, 2023, the KM3NeT/ARCA telescope detected a neutrino candidate with an estimated energy in the hundreds of PeVs. In this article, the observation of this ultra-high-energy neutrino is discussed in light of null observations above tens of PeV from the IceCube and Pierre Auger observatories. Performing a joint fit of all experiments under the assumption of an isotropic E−2 flux, the best-fit single-flavour flux normalisation is E2Φ1fν+ν¯ = 7.5 × 10−10 GeVcm−2s−1sr−1 in the 90% energy range of the KM3NeT event. Furthermore, the ultra-high-energy data are then fit together with the IceCube measurements at lower energies, either with a single power law or with a broken power law, allowing for the presence of a new component in the spectrum. The joint fit including non-observations by other experiments in the ultra-high-energy region shows a slight preference for a break in the PeV regime if the "High-Energy Starting Events" sample is included, and no such preference for the other two IceCube samples investigated. A stronger preference for a break appears if only the KM3NeT data is considered in the ultra-high-energy region, though the flux resulting from such a fit would be inconsistent with null observations from IceCube and Pierre Auger. In all cases, the observed tension between KM3NeT and other datasets is of the order of 2.5σ − 3σ, and increased statistics are required to resolve this apparent tension and better characterise the neutrino landscape at ultra-high energies. Copyright © 2025, The Authors. All rights reserved.

关键词： Neutrons

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Study of the flexibility of a learning analytics tool to evaluate teamwork competence acquisition in different contexts

Study of the flexibility of a learning analytics tool to eva...

引用

2017 Learning Analytics Summer Institute Spain: Advances in Learning Analytics, LASI-SPAIN 2017

作者： Conde, Miguel Ángel García-Peñalvo, Francisco J. Fidalgo-Blanco, Ángel Sein-Echaluce, María Luisa Department of Mechanics Computer Science and Aerospace Engineering Robotics Group University of León - Campus de Vegazana S/N León24071 Spain Research Institute for Educational Sciences GRIAL research group Faculty of Science - Plaza de Los Caídos S/N. 37008 Salamanca University of Salamanca Spain Laboratory of Innovation in Information Technologies Politechnical University of Madrid Calle de Ríos Rosas 21 Madrid28003 Spain Department of Applied Mathematics Campus Rio Ebro University of Zaragoza Calle de María de Luna 3 Zaragoza50018 Spain

Learning analytics tools and methodologies aim to facilitate teachers and/or decision makers with information and knowledge about what is happening in virtual learning environments in a straightforward and effortless way. However, it is necessary to apply these tools and methodologies in different contexts with a similar success, that is, that they should be flexible and portable enough. There exist several learning analytics tools that only works properly with very specific versions of learning platforms. In this paper, the authors aim to evaluate the flexibility and portability of a methodology and a learning analytics tool that supports individual assessment of teamwork competence. In order to do so the methodology and the tool are applied in a similar course from two different academic contexts. After the experiment, it is possible to see that the learning analytics tool seems to work properly and the suggested new functionalities are similar in both contexts. The methodology can be also applied but results could be improved if some meetings are carried out to check how team works are progressing with their tasks.

关键词： computer aided instruction

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Optoelectronic Devices: Thin Metallic Heat Sink for Interfacial Thermal Management in Biointegrated Optoelectronic Devices (Adv. Mater. Technol. 11/2018)

引用

Advanced Materials Technologies 2018年第11期3卷

作者： Han Hee Jung Juwon Song Shuang Nie Han Na Jung Min Seok Kim Jae-Woong Jeong Young Min Song Jizhou Song Kyung-In Jang Department of Robotics Engineering Department of Information and Communication Engineering Brain Engineering Convergence Center Daegu Gyeongbuk Institute of Science and Technology Daegu 49288 Republic of Korea Department of Engineering Mechanics Soft Matter Research Center and Key Laboratory of Soft Machines and Smart Devices of Zhejiang Province Zhejiang University Hangzhou 310027 China School of Electrical Engineering and Computer Science Gwangju Institute of Science and Technology 123 Cheomdan-gwagiro Buk-gu Gwangju 61005 Republic of Korea School of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon 34141 Republic of Korea

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Author Correction: Observation of an ultra-high-energy cosmic neutrino with KM3NeT

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Nature 2025年第8057期640卷 E3页

作者： S. Aiello R. Bruno G. Ferrara E. Leonora F. Longhitano N. Randazzo A. Sinopoulou I. Tosta e Melo A. Albert D. Drouhin T. Pradier A. R. Alhebsi S. Thoudam A. van Vliet M. Alshamsi V. Bertin M. Breuhaus J. Brunner J. Busto L. Cerisy P. Coyle B. De Martino D. Dornic J.-G. Ducoin A. Enzenhöfer S. Henry D. Joly S. Lancelin S. Le Stum N. Lumb F. Magnani C. Paries M. Perrin-Terrin G. Vannoye S. Alves Garre A. Bariego-Quintana D. Calvo V. Cecchini A. Garcia Soto S. R. Gozzini J. J. Hernández-Rey A. Lazo N. Lessing J. Palacios González E. J. Pastor Gomez J. Prado D. Real A. Šaina F. Salesa Greus A. Sánchez Losa J. D. Zornoza J. Zúñiga A. Ambrosone M. Bendahman M. Benhassi C. Bozza R. M. Bozza R. Buompane A. Condorelli A. De Benedittis L. A. Fusco L. Gialanella W. Idrissi Ibnsalih A. Manfreda A. Marinelli F. Marzaioli S. Mastroianni G. Miele P. Migliozzi M. L. Mitsou C. M. Mollo L. Morales-Gallegos M. R. Musone V. Oliviero C. Poirè I. C. Rea A. Simonelli B. Spisso D. Vivolo F. Ameli A. Capone S. Celli I. Di Palma S. Gagliardini M. Mastrodicasa C. A. Nicolau A. Tudorache A. Veutro A. Zegarelli M. Andre M. Anghinolfi F. Badaracco B. Caiffi V. Ellajosyula C. Guidi V. Kulikovskiy L. Malerba M. Marconi B. Ó Fearraigh V. Parisi A. Romanov M. Sanguineti M. Taiuti S. Zavatarelli L. Aphecetche F. Bretaudeau R. Dallier V. Decoene L. Martin M. Ardid S. Ardid J. García Méndez C. A. Quiroz-Rangel C. Argüelles N. Kamp A. Y. Wen H. Atmani J. Boumaaza A. Eddymaoui Y. Tayalati J. Aublin B. Baret Y. Becherini T. Cartraud J. A. B. Coelho A. Coleiro S. Colonges A. Creusot C. Donzaud M. Eff S. El Hedri I. Goos P. Goswami A. Ilioni A. Kouchner M. Lindsey Clark E. Oukacha S. Peña Martínez R. Pestes A. Sharma B. Trocmé V. Van Elewyck C. Verilhac I. Lhenry-Yvon L. Bailly-Salins M. Bennani B. Guillon M. Labalme C. Lastoria G. Lehaut I. Mozun Mateo V. Pestel A. Vacheret Z. Bardačová E. Eckerová F. Mamedov Y. Shitov I. Štekl R. Dvornický F. Šimkovic F. Benfenati Gualandi F. Carenini P. Castaldi T. Chiarusi I. Del Rosso G. Levi A. Margiotta R. Muller INFN Sezione di Catania (INFN-CT) Catania Italy INFN Laboratori Nazionali del Sud (LNS) Catania Italy Dipartimento di Fisica e Astronomia “Ettore Majorana” Università di Catania (INFN-CT) Catania Italy Université de Strasbourg CNRS IPHC UMR 7178 Strasbourg France Université de Haute Alsace Mulhouse France Department of Physics Khalifa University Abu Dhabi United Arab Emirates Aix Marseille Université CNRS/IN2P3 CPPM Marseille France IFIC - Instituto de Física Corpuscular (CSIC - Universitat de València) Paterna Spain INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Napoli Italy Università di Napoli “Federico II” Dip. Scienze Fisiche “E. Pancini” Complesso Universitario di Monte S. Angelo Napoli Italy Dipartimento di Matematica e Fisica Università degli Studi della Campania “Luigi Vanvitelli” Caserta Italy Dipartimento di Fisica Università di Salerno e INFN Gruppo Collegato di Salerno Fisciano Italy INFN Sezione di Roma Roma Italy Dipartimento di Fisica Università La Sapienza Roma Italy Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Universitat Politècnica de Catalunya Vilanova i la Geltrú Spain INFN Sezione di Genova Genova Italy Università di Genova Genova Italy LPC CAEN Normandie Université ENSICAEN UNICAEN CNRS/IN2P3 Caen France Subatech IMT Atlantique IN2P3-CNRS Nantes Université Nantes France Instituto de Investigación para la Gestión Integrada de las Zonas Costeras Universitat Politècnica de València Gandia Spain Department of Physics Harvard University Cambridge MA USA Laboratory for Particle Physics and Cosmology Lyman Laboratory Harvard University Cambridge MA USA Faculty of Sciences University Mohammed V in Rabat Rabat Morocco Institute of Applied Physics Mohammed VI Polytechnic University Ben Guerir Morocco Astroparticule et Cosmologie Université Paris Cité CNRS Paris France Institut Universitaire de France Paris France Institute of Experimental and Applied Physics

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DAC-h3: A proactive robot cognitive architecture to acquire and express knowledge about the world and the self

arXiv

引用

arXiv 2017年

作者： Moulin-Frier, Clément Fischer, Tobias Petit, Maxime Pointeau, Grégoire Puigbo, Jordi-Ysard Pattacini, Ugo Low, Sock Ching Camilleri, Daniel Nguyen, Phuong Hoffmann, Matej Chang, Hyung Jin Zambelli, Martina Mealier, Anne-Laure Damianou, Andreas Metta, Giorgio Prescott, Tony J. Demiris, Yiannis Dominey, Peter Ford Verschure, Paul F.M.J. Laboratory for Synthetic Perceptive Emotive and Cognitive Systems Universitat Pompeu Fabra Barcelona08002 Spain Barcelona Spain Personal Robotics Laboratory Department of Electrical and Electronic Engineering Imperial College London SW7 2AZ United Kingdom Robot Cognition Laboratory INSERM U846 Stem Cell and Brain Research Institute Bron69675 France Italian Institute of Technology iCub Facility Via Morego 30 Genova Italy Department of Cybernetics Faculty of Electrical Engineering Czech Technical University in Prague Department of Computer Science University of Sheffield United Kingdom

This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in human-robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users. Copyright © 2017, The Authors. All rights reserved.

关键词： Human robot interaction

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Template-based human supervised robot task programming

Template-based human supervised robot task programming

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Xianchao Long Taskin Padir Robotics and Intelligent Vehicles Research Laboratory (RIVeR Lab) Department of Electrical and Computer Engineering Northeastern University Boston Massachussetts United States

ISBN: (纸本)9781509037636

Motions of a robot interacting with its environment can be described by a set of constraints. This paper introduces an approach, called motion template, which can quickly program and compose the constraints for the motion planner to generate the trajectory. Two types of motion templates, grasp and turn, are specifically described to explain the details of the technique. The reusability and shareability properties of the motion template are demonstrated using a variety of the motion planning applications across different robot platforms. A motion template framework is used to implement the motion template with the trajectory optimization.

关键词： jigs(templates) Robot trajectory optimization Programming

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