Freek Stulp

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Michael BeetzIntitute for Artificial Intelligence, Computer Science Department, University of BremenEmail confirmado em cs.uni-bremen.de
Stefan SchaalRobotics, Machine Learning, AI, NeuroscienceEmail confirmado em google.com
Evangelos TheodorouGeorgia Institute of Technology & Amazon SEASEmail confirmado em ae.gatech.edu
Olivier SigaudProfessor in Computer Science, Sorbonne UniversitéEmail confirmado em upmc.fr
Alin Albu-SchäfferDLR-German Aerospace Center, Institute of Robotics and Mechatronics; TU Munich, Dept. of InformaticsEmail confirmado em dlr.de
Jonas BuchliDeepMindEmail confirmado em google.com
Daniel LeidnerGerman Aerospace Center (DLR)Email confirmado em dlr.de
Bernd RadigTechnical University of MunichEmail confirmado em in.tum.de
Antonin RaffinDLREmail confirmado em dlr.de
Gabriel QuereGerman Aerospace Center (DLR)Email confirmado em dlr.de
Samuel BustamanteCognitive Robotics department, Robotics and Mechatronics Center, German Aerospace Center (DLR)Email confirmado em dlr.de
Gennaro RaiolaNASA Jet Propulsion Laboratory (JPL)Email confirmado em jpl.nasa.gov
João SilvérioGerman Aerospace Center (DLR)Email confirmado em dlr.de
Alexis MaldonadoResearcher, Artificial Intelligence - Universitaet BremenEmail confirmado em cs.uni-bremen.de
Jörn VogelGerman Aerospace Center (DLR)Email confirmado em dlr.de
Korbinian NottensteinerGerman Aerospace Center (DLR), Institute of Robotics and MechatronicsEmail confirmado em dlr.de
Franz SteinmetzBosch RexrothEmail confirmado em dlr.de
Bernhard WeberEmail confirmado em dlr.de
Dr. rer. nat. Ismael Valentín Rodríguez...Agile RobotsEmail confirmado em agile-robots.com
Serena IvaldiResearch director, INRIAEmail confirmado em inria.fr

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Freek Stulp

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

Email confirmado em dlr.de

Robotics Artificial Intelligence Machine Learning


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Learning variable impedance control J Buchli, F Stulp, E Theodorou, S Schaal The International Journal of Robotics Research 30 (7), 820-833, 2011	431	2011
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	362*	2023
Many regression algorithms, one unified model: A review F Stulp, O Sigaud Neural Networks 69, 60-79, 2015	279	2015
Path integral policy improvement with covariance matrix adaptation F Stulp, O Sigaud arXiv preprint arXiv:1206.4621, 2012	270	2012
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	260	2012
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	204	2019
Robot skill learning: From reinforcement learning to evolution strategies F Stulp, O Sigaud Paladyn, Journal of Behavioral Robotics 4 (1), 49-61, 2013	182	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	111	2011
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration⁰ A O’Neill, A Rehman, A Maddukuri, A Gupta, A Padalkar, A Lee, A Pooley, ... 2024 IEEE International Conference on Robotics and Automation (ICRA), 6892-6903, 2024	109	2024
Policy search in continuous action domains: an overview O Sigaud, F Stulp Neural Networks 113, 28-40, 2019	109	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
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	102	2013
Variable impedance control a reinforcement learning approach J Buchli, E Theodorou, F Stulp, S Schaal Robotics: Science and Systems VI 153, 2011	99	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	96	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	95	2008
Smooth Exploration for Robotic Reinforcement Learning A Raffin, J Kober, F Stulp 5th Annual Conference on Robot Learning, 2021	90	2021
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	87	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	72	2012

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