Univ.-Prof. Dr. Elmar Rueckert

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	All	Since 2019
Citations	962	724
h-index	17	15
i10-index	26	23

160

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20122013201420152016201720182019202020212022202320246 9 24 25 35 63 67 88 110 149 124 151 102

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Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKIVerified email at ias.tu-darmstadt.de
Gerhard NeumannProfessor, Karlsruhe Institute of Technology (KIT)Verified email at robot-learning.de
Daniel TannebergSenior Scientist @ Honda Research Institute EU, PhD from IAS @ TU DarmstadtVerified email at robot-learning.de
Nils RottmannUniversity of LuebeckVerified email at rob.uni-luebeck.de
Roberto CalandraProfessor, TU Dresden / Centre for Tactile Internet with Human-in-the-Loop (CeTI)Verified email at tu-dresden.de
Honghu XueUniversity of LübeckVerified email at uni-luebeck.de
Serena IvaldiResearch director, INRIAVerified email at inria.fr
Philipp BeckerleFAU Erlangen-NürnbergVerified email at fau.de
Alexandros ParaschosVolkswagen AGVerified email at argmax.ai
David KappelRuhr-Universität BochumVerified email at rub.de
Andrea d'AvellaUniversity of Rome Tor Vergata and IRCCS Fondazione Santa LuciaVerified email at hsantalucia.it
Dejan PecevskiAI/ML Department, Jumio Corp., Vienna, AustriaVerified email at jumio.com
Vedant DaveMontanuniversität LeobenVerified email at unileoben.ac.at
Marc DeisenrothUniversity College London and The Alan Turing InstituteVerified email at ucl.ac.uk
Svenja StarkIAS, TU DarmstadtVerified email at ias.informatik.tu-darmstadt.de
Marc ToussaintProfessor of Computer Science, TU Berlin, GermanyVerified email at tu-berlin.de
Wolfgang MaassProfessor of Computer Science, Graz University of TechnologyVerified email at igi.tugraz.at
Fotios LygerakisDoctoral StudentVerified email at unileoben.ac.at
Giuseppe OrioloDipartimento di Ingegneria Informatica, Automatica e Gestionale, Sapienza Università di RomaVerified email at diag.uniroma1.it
Valerio ModugnoAssociate Lecturer, University College London (UCL)Verified email at ucl.ac.uk

Univ.-Prof. Dr. Elmar Rueckert

Chair of Cyber-Physical-Systems at Montanuniversität Leoben

Verified email at ai-lab.science - Homepage

Neurorobotics Deep Learning Reinforcement Learning Human Motor Control


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems E Rückert, A d'Avella Frontiers in computational neuroscience 7, 138, 2013	87	2013
Recurrent spiking networks solve planning tasks E Rueckert, D Kappel, D Tanneberg, D Pecevski, J Peters Scientific reports 6, 21142, 2016	84	2016
Learning inverse dynamics models in o (n) time with lstm networks E Rueckert, M Nakatenus, S Tosatto, J Peters 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids …, 2017	81	2017
Learning inverse dynamics models with contacts R Calandra, S Ivaldi, MP Deisenroth, E Rueckert, J Peters 2015 IEEE International Conference on Robotics and Automation (ICRA), 3186-3191, 2015	66	2015
A low-cost sensor glove with vibrotactile feedback and multiple finger joint and hand motion sensing for human-robot interaction P Weber, E Rueckert, R Calandra, J Peters, P Beckerle 2016 25th IEEE International Symposium on Robot and Human Interactive …, 2016	62	2016
Learned Graphical Models for Probabilistic Planning Provide a New Class of Movement Primitives E Rückert, G Neumann, M Toussaint, W Maass Frontiers in Computational Neuroscience 6 (97), 2012	57	2012
Extracting Low-Dimensional Control Variables for Movement Primitives E Rueckert, J Mundo, A Paraschos, J Peters, G Neumann Proc. IEEE Int. Conf. on Robotics and Automation (ICRA), 2015	48	2015
Learning soft task priorities for control of redundant robots V Modugno, G Neumann, E Rueckert, G Oriolo, J Peters, S Ivaldi 2016 IEEE International Conference on Robotics and Automation (ICRA), 221-226, 2016	42	2016
Intrinsic motivation and mental replay enable efficient online adaptation in stochastic recurrent networks D Tanneberg, J Peters, E Rueckert Neural networks 109, 67-80, 2019	31	2019
Skid raw: Skill discovery from raw trajectories D Tanneberg, K Ploeger, E Rueckert, J Peters IEEE robotics and automation letters 6 (3), 4696-4703, 2021	27	2021
Stochastic optimal control methods for investigating the power of morphological computation EA Rückert, G Neumann Artificial Life 19 (1), 115-131, 2013	25	2013
Probabilistic movement primitives under unknown system dynamics A Paraschos, E Rueckert, J Peters, G Neumann Advanced Robotics 32 (6), 297-310, 2018	24	2018
Model-free probabilistic movement primitives for physical interaction A Paraschos, E Rueckert, J Peters, G Neumann 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015	24	2015
Simultaneous localisation and mapping for mobile robots with recent sensor technologies EA Rückert na, 2009	22	2009
Probabilistic movement models show that postural control precedes and predicts volitional motor control E Rueckert, J Čamernik, J Peters, J Babič Scientific reports 6 (1), 28455, 2016	20	2016
Using deep reinforcement learning with automatic curriculum learning for mapless navigation in intralogistics H Xue, B Hein, M Bakr, G Schildbach, B Abel, E Rueckert Applied Sciences 12 (6), 3153, 2022	18	2022
Ros-mobile: An android application for the robot operating system N Rottmann, N Studt, F Ernst, E Rueckert arXiv preprint arXiv:2011.02781, 2020	17	2020
Inverse reinforcement learning via nonparametric spatio-temporal subgoal modeling A Šošić, E Rueckert, J Peters, AM Zoubir, H Koeppl Journal of Machine Learning Research 19 (69), 1-45, 2018	17	2018
Model estimation and control of compliant contact normal force M Azad, V Ortenzi, HC Lin, E Rueckert, M Mistry 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids …, 2016	15	2016
Experience reuse with probabilistic movement primitives S Stark, J Peters, E Rueckert 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019	12	2019

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