Danica Kragic

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Citations	23119	11542
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Mårten BjörkmanKTH Royal Institute of TechnologyAdresse e-mail validée de kth.se
Henrik Iskov ChristensenDirector / Professor @ UCSDAdresse e-mail validée de ucsd.edu
Florian T. PokornyAssociate Professor, KTH Royal Institute of TechnologyAdresse e-mail validée de kth.se
Hedvig Kjellström (Sidenbladh)Professor at KTH Royal Institute of Technology, SwedenAdresse e-mail validée de kth.se
Jeannette BohgAssistant Professor, Stanford UniversityAdresse e-mail validée de stanford.edu
Javier RomeroReality Labs Research, MetaAdresse e-mail validée de meta.com
Kaiyu HangRice UniversityAdresse e-mail validée de rice.edu
Yiannis KarayiannidisAssociate Professor, Automatic Control, LTH, Lund UniversityAdresse e-mail validée de control.lth.se
Yasemin BekiroğluChalmers University of Technology, University College London (UCL)Adresse e-mail validée de chalmers.se
Ville KyrkiProfessor at Aalto UniversityAdresse e-mail validée de aalto.fi
Judith BütepageSenior Research Engineer, SEED @ EAAdresse e-mail validée de kth.se
Tamim AsfourKarlsruhe Institute of Technology (KIT)Adresse e-mail validée de kit.edu
Patric JensfeltKTH Royal Institute of TechnologyAdresse e-mail validée de kth.se
Renaud DetryKU LeuvenAdresse e-mail validée de kuleuven.be
Aude BillardFull Professor, EPFLAdresse e-mail validée de epfl.ch
Ken GoldbergProfessor, UC Berkeley and UCSFAdresse e-mail validée de berkeley.edu
Volker KruegerLund UniversityAdresse e-mail validée de cs.lth.se
Dimos DimarogonasKTH Royal Institute of TechnologyAdresse e-mail validée de kth.se
Aleš UdeJožef Stefan InstituteAdresse e-mail validée de ijs.si
Püren GülerEricssonAdresse e-mail validée de ericsson.com

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Danica Kragic

Professor of Computer Science, KTH - Royal Institute of Technology

Adresse e-mail validée de kth.se - Page d'accueil

robotics AI robot vision robot learning


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Data-driven grasp synthesis—a survey J Bohg, A Morales, T Asfour, D Kragic IEEE Transactions on robotics 30 (2), 289-309, 2013	1290	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	1174	2015
Trends and challenges in robot manipulation A Billard, D Kragic Science 364 (6446), eaat8414, 2019	895	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	641	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	616	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	511	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	419	2009
Survey on visual servoing for manipulation D Kragic, HI Christensen Computational Vision and Active Perception Laboratory, Fiskartorpsv 15, 2002, 2002	377	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	369	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	304	2011
Modeling, learning, perception, and control methods for deformable object manipulation H Yin, A Varava, D Kragic Science Robotics 6 (54), eabd8803, 2021	289	2021
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	252	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	250	2008
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
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	238	2007
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	234	2005
Deep learning approaches to grasp synthesis: A review R Newbury, M Gu, L Chumbley, A Mousavian, C Eppner, J Leitner, J Bohg, ... IEEE Transactions on Robotics 39 (5), 3994-4015, 2023	185	2023
Grasp recognition for programming by demonstration S Ekvall, D Kragic Proceedings of the 2005 IEEE International Conference on Robotics and …, 2005	180	2005
Learning grasping points with shape context J Bohg, D Kragic Robotics and Autonomous Systems 58 (4), 362-377, 2010	179	2010
Interactive, Collaborative Robots: Challenges and Opportunities. D Kragic, J Gustafson, H Karaoguz, P Jensfelt, R Krug IJCAI, 18-25, 2018	174	2018

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