Danica Kragic

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	Todos	Desde 2019
Citações	22242	12184
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Mårten BjörkmanKTH Royal Institute of TechnologyEmail confirmado em kth.se
Henrik Iskov ChristensenDirector / Professor @ UCSDEmail confirmado em ucsd.edu
Hedvig Kjellström (Sidenbladh)Professor at KTH Royal Institute of Technology, SwedenEmail confirmado em kth.se
Florian T. PokornyAssociate Professor, KTH Royal Institute of TechnologyEmail confirmado em kth.se
Javier RomeroReality Labs Research, MetaEmail confirmado em tuebingen.mpg.de
Jeannette BohgAssistant Professor, Stanford UniversityEmail confirmado em stanford.edu
Kaiyu HangRice UniversityEmail confirmado em rice.edu
Yiannis KarayiannidisAssociate Professor, Automatic Control, LTH, Lund UniversityEmail confirmado em kth.se
Yasemin BekiroğluChalmers University of Technology, University College London (UCL)Email confirmado em chalmers.se
Ville KyrkiProfessor at Aalto UniversityEmail confirmado em aalto.fi
Judith BütepageSenior Research Engineer, SEED @ EAEmail confirmado em kth.se
Tamim AsfourKarlsruhe Institute of Technology (KIT)Email confirmado em kit.edu
Patric JensfeltKTH Royal Institute of TechnologyEmail confirmado em kth.se
Renaud DetryKU LeuvenEmail confirmado em kuleuven.be
Aude BillardFull Professor, EPFLEmail confirmado em epfl.ch
Ken GoldbergProfessor, UC Berkeley and UCSFEmail confirmado em berkeley.edu
Volker KruegerLund UniversityEmail confirmado em cs.lth.se
Dimos DimarogonasKTH Royal Institute of TechnologyEmail confirmado em kth.se
Aleš UdeJožef Stefan InstituteEmail confirmado em ijs.si
Michael J. BlackMax Planck Institute for Intelligent SystemsEmail confirmado em tuebingen.mpg.de

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Danica Kragic

Professor of Computer Science, KTH - Royal Institute of Technology

Email confirmado em kth.se - Página inicial

robotics AI robot vision robot learning


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Data-driven grasp synthesis—a survey J Bohg, A Morales, T Asfour, D Kragic IEEE Transactions on robotics 30 (2), 289-309, 2013	1262	2013
The grasp taxonomy of human grasp types T Feix, J Romero, HB Schmiedmayer, AM Dollar, D Kragic IEEE Transactions on human-machine systems 46 (1), 66-77, 2015	1102	2015
Trends and challenges in robot manipulation A Billard, D Kragic Science 364 (6446), eaat8414, 2019	789	2019
Dual arm manipulation—A survey C Smith, Y Karayiannidis, L Nalpantidis, X Gratal, P Qi, DV Dimarogonas, ... Robotics and Autonomous systems 60 (10), 1340-1353, 2012	608	2012
Combating COVID-19—The role of robotics in managing public health and infectious diseases GZ Yang, B J. Nelson, RR Murphy, H Choset, H Christensen, S H. Collins, ... Science robotics 5 (40), eabb5589, 2020	594	2020
Deep representation learning for human motion prediction and classification J Butepage, MJ Black, D Kragic, H Kjellstrom Proceedings of the IEEE conference on computer vision and pattern …, 2017	520	2017
A comprehensive grasp taxonomy T Feix, R Pawlik, HB Schmiedmayer, J Romero, D Kragic Robotics, science and systems: workshop on understanding the human hand for …, 2009	412	2009
Survey on visual servoing for manipulation D Kragic, HI Christensen Computational Vision and Active Perception Laboratory, Fiskartorpsv 15, 2002, 2002	372	2002
Interactive perception: Leveraging action in perception and perception in action J Bohg, K Hausman, B Sankaran, O Brock, D Kragic, S Schaal, ... IEEE Transactions on Robotics 33 (6), 1273-1291, 2017	358	2017
Visual object-action recognition: Inferring object affordances from human demonstration H Kjellström, J Romero, D Kragić Computer Vision and Image Understanding 115 (1), 81-90, 2011	306	2011
Design of a flexible tactile sensor for classification of rigid and deformable objects A Drimus, G Kootstra, A Bilberg, D Kragic Robotics and Autonomous Systems 62 (1), 3-15, 2014	248	2014
Minimum volume bounding box decomposition for shape approximation in robot grasping K Huebner, S Ruthotto, D Kragic 2008 IEEE International Conference on Robotics and Automation, 1628-1633, 2008	246	2008
Modeling, learning, perception, and control methods for deformable object manipulation H Yin, A Varava, D Kragic Science Robotics 6 (54), eabd8803, 2021	244	2021
Assessing grasp stability based on learning and haptic data Y Bekiroglu, J Laaksonen, JA Jorgensen, V Kyrki, D Kragic IEEE Transactions on Robotics 27 (3), 616-629, 2011	243	2011
Human-machine collaborative systems for microsurgical applications D Kragic, P Marayong, M Li, AM Okamura, GD Hager The international journal of robotics research 24 (9), 731-741, 2005	233	2005
The meaning of action: A review on action recognition and mapping V Krüger, D Kragic, A Ude, C Geib Advanced robotics 21 (13), 1473-1501, 2007	232	2007
Grasp recognition for programming by demonstration S Ekvall, D Kragic Proceedings of the 2005 IEEE International Conference on Robotics and …, 2005	181	2005
Learning grasping points with shape context J Bohg, D Kragic Robotics and Autonomous Systems 58 (4), 362-377, 2010	178	2010
Adaptive virtual fixtures for machine-assisted teleoperation tasks D Aarno, S Ekvall, D Kragic Proceedings of the 2005 IEEE international conference on robotics and …, 2005	173	2005
Interactive grasp learning based on human demonstration S Ekvall, D Kragic Robotics and Automation, 2004. Proceedings. ICRA'04. 2004 IEEE International …, 2004	171	2004

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