Freek Stulp

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Michael BeetzIntitute for Artificial Intelligence, Computer Science Department, University of BremenVerified email at cs.uni-bremen.de
Stefan SchaalRobotics, Machine Learning, AI, NeuroscienceVerified email at google.com
Evangelos TheodorouGeorgia Institute of Technology & Amazon SEASVerified email at ae.gatech.edu
Olivier SigaudProfessor in Computer Science, Sorbonne UniversitéVerified email at upmc.fr
Jonas BuchliDeepMindVerified email at google.com
Alin Albu-SchäfferDLR-German Aerospace Center, Institute of Robotics and Mechatronics; TU Munich, Dept. of InformaticsVerified email at dlr.de
Daniel LeidnerGerman Aerospace Center (DLR)Verified email at dlr.de
Bernd RadigTechnical University of MunichVerified email at in.tum.de
Antonin RaffinDLRVerified email at dlr.de
Gabriel QuereGerman Aerospace Center (DLR)Verified email at dlr.de
Gennaro RaiolaNASA Jet Propulsion Laboratory (JPL)Verified email at jpl.nasa.gov
Samuel BustamanteCognitive Robotics department, Robotics and Mechatronics Center, German Aerospace Center (DLR)Verified email at dlr.de
Alexis MaldonadoResearcher, Artificial Intelligence - Universitaet BremenVerified email at cs.uni-bremen.de
Jörn VogelGerman Aerospace Center (DLR)Verified email at dlr.de
Korbinian NottensteinerGerman Aerospace Center (DLR), Institute of Robotics and MechatronicsVerified email at dlr.de
Franz SteinmetzBosch RexrothVerified email at dlr.de
Bernhard WeberVerified email at dlr.de
Ismael Valentín Rodríguez BrenaAgile RobotsVerified email at agile-robots.com
Serena IvaldiResearch director, INRIAVerified email at inria.fr
Peter PastorRoboticist, GoogleVerified email at google.com

Freek Stulp

Head of Department of Cognitive Robotics, German Aerospace Center (DLR)

Verified email at dlr.de

Robotics Artificial Intelligence Machine Learning


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Learning variable impedance control J Buchli, F Stulp, E Theodorou, S Schaal The International Journal of Robotics Research 30 (7), 820-833, 2011	414	2011
Path integral policy improvement with covariance matrix adaptation F Stulp, O Sigaud arXiv preprint arXiv:1206.4621, 2012	264	2012
Many regression algorithms, one unified model: A review F Stulp, O Sigaud Neural Networks 69, 60-79, 2015	259	2015
Reinforcement learning with sequences of motion primitives for robust manipulation F Stulp, EA Theodorou, S Schaal IEEE Transactions on robotics 28 (6), 1360-1370, 2012	251	2012
Open X-Embodiment: Robotic learning datasets and RT-X models A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, A Irpan, A Khazatsky, ... arXiv preprint arXiv:2310.08864, 2023	202	2023
A survey on policy search algorithms for learning robot controllers in a handful of trials K Chatzilygeroudis, V Vassiliades, F Stulp, S Calinon, JB Mouret IEEE Transactions on Robotics 36 (2), 328-347, 2019	191	2019
Robot skill learning: From reinforcement learning to evolution strategies F Stulp, O Sigaud Paladyn, Journal of Behavioral Robotics 4 (1), 49-61, 2013	173	2013
Learning to grasp under uncertainty F Stulp, E Theodorou, J Buchli, S Schaal 2011 IEEE International Conference on Robotics and Automation, 5703-5708, 2011	119	2011
Hierarchical reinforcement learning with movement primitives F Stulp, S Schaal 2011 11th IEEE-RAS International Conference on Humanoid Robots, 231-238, 2011	107	2011
Policy search in continuous action domains: an overview O Sigaud, F Stulp Neural Networks 113, 28-40, 2019	106	2019
Movement segmentation using a primitive library F Meier, E Theodorou, F Stulp, S Schaal 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2011	106	2011
Policy improvement methods: Between black-box optimization and episodic reinforcement learning F Stulp, O Sigaud	105	2012
Variable impedance control a reinforcement learning approach J Buchli, E Theodorou, F Stulp, S Schaal Robotics: Science and Systems VI 153, 2011	98	2011
Learning compact parameterized skills with a single regression F Stulp, G Raiola, A Hoarau, S Ivaldi, O Sigaud Humanoid Robots (Humanoids), 2013 13th IEEE-RAS International Conference on …, 2013	97	2013
From dynamic movement primitives to associative skill memories P Pastor, M Kalakrishnan, F Meier, F Stulp, J Buchli, E Theodorou, ... Robotics and Autonomous Systems 61 (4), 351-361, 2013	97	2013
The assistive kitchen—a demonstration scenario for cognitive technical systems M Beetz, F Stulp, B Radig, J Bandouch, N Blodow, M Dolha, A Fedrizzi, ... RO-MAN 2008-The 17th IEEE International Symposium on Robot and Human …, 2008	94	2008
Generality and legibility in mobile manipulation M Beetz, F Stulp, P Esden-Tempski, A Fedrizzi, U Klank, I Kresse, ... Autonomous Robots 28 (1), 21-44, 2010	84	2010
Model-free reinforcement learning of impedance control in stochastic environments F Stulp, J Buchli, A Ellmer, M Mistry, EA Theodorou, S Schaal IEEE Transactions on Autonomous Mental Development 4 (4), 330-341, 2012	71	2012
Learning local objective functions for robust face model fitting M Wimmer, F Stulp, S Pietzsch, B Radig IEEE Transactions on Pattern Analysis and Machine Intelligence 30 (8), 1357-1370, 2008	69	2008
Smooth Exploration for Robotic Reinforcement Learning A Raffin, J Kober, F Stulp 5th Annual Conference on Robot Learning, 2021	67	2021

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