Manuel Mühlig

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Michael GiengerHonda Research Institute EuropeDirección de correo verificada de honda-ri.de
Jochen J. SteilProfessor of Robotics, Technische Universität BraunschweigDirección de correo verificada de tu-braunschweig.de
Anna-Lisa VollmerMedical School OWL & CITEC - Bielefeld UniversityDirección de correo verificada de uni-bielefeld.de
Karola PitschInstitute of Communication Studies, University of Duisburg-EssenDirección de correo verificada de uni-due.de
Nick HawesOxford Robotics Institute, University of OxfordDirección de correo verificada de robots.ox.ac.uk
Charlie StreetSchool of Computer Science, University of BirminghamDirección de correo verificada de charliestreet.net
Bruno LacerdaOxford Robotics Institute - University of OxfordDirección de correo verificada de robots.ox.ac.uk
Takahide YoshiikeDirección de correo verificada de honda-ri.jp
Britta WredeMedical Assistance Systems, Bielefeld UniversityDirección de correo verificada de techfak.uni-bielefeld.de
Stephan HaslerHonda Research Institute Europe GmbHDirección de correo verificada de honda-ri.de
Joerg DeigmoellerHonda Research Institute Europe GmbHDirección de correo verificada de honda-ri.de
Nils EineckeHonda Research Institute Europe GmbHDirección de correo verificada de honda-ri.de
Chao WangHonda Research Institute EuropeDirección de correo verificada de honda-ri.de
Ahmed R. SadikHonda Research Institute - EUDirección de correo verificada de honda-ri.de
Michal StaniaszekOxford Robotics Institute, University of OxfordDirección de correo verificada de robots.ox.ac.uk
Changhyun SungHyundai Motor CompanyDirección de correo verificada de hyundai.com
Angelo CangelosiProfessor of Machine Learning and Robotics, University of ManchesterDirección de correo verificada de manchester.ac.uk
Soshi IbaHonda Research Institute USADirección de correo verificada de ieee.org

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Manuel Mühlig

Principal Engineer, Honda Research Institute Europe GmbH

Dirección de correo verificada de muehlig.eu - Página principal


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Task-level imitation learning using variance-based movement optimization M Mühlig, M Gienger, S Hellbach, JJ Steil, C Goerick 2009 IEEE International Conference on Robotics and Automation (ICRA 2009 …, 2009	141	2009
Interactive imitation learning of object movement skills M Mühlig, M Gienger, JJ Steil Autonomous Robots 32, 97-114, 2012	93	2012
Automatic selection of task spaces for imitation learning M Mühlig, M Gienger, JJ Steil, C Goerick 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2009	59	2009
Robot with automatic selection of task-specific representations for imitation learning M Gienger, M Mühlig, J Steil, HRIE Gmbh US Patent 8,571,714, 2013	57	2013
Robots show us how to teach them: Feedback from robots shapes tutoring behavior during action learning AL Vollmer, M Mühlig, JJ Steil, K Pitsch, J Fritsch, KJ Rohlfing, B Wrede PloS one 9 (3), e91349, 2014	55	2014
Robot feedback shapes the tutor’s presentation: How a robot’s online gaze strategies lead to micro-adaptation of the human’s conduct K Pitsch, AL Vollmer, M Mühlig Interaction Studies 14 (2), 268-296, 2013	42	2013
Human-robot interaction for learning and adaptation of object movements M Mühlig, M Gienger, JJ Steil 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2010	26	2010
Adaptive movement sequences and predictive decisions based on hierarchical dynamical systems T Luksch, M Gienger, M Mühlig, T Yoshiike 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2012	23	2012
Multi-robot planning under uncertainty with congestion-aware models C Street, B Lacerda, M Mühlig, N Hawes Association for Computing Machinery, 2020	22	2020
Congestion-aware policy synthesis for multirobot systems C Street, S Pütz, M Mühlig, N Hawes, B Lacerda IEEE Transactions on Robotics 38 (1), 262-280, 2021	21	2021
Method for improving operation of a robot M Mühlig, M Gienger, A Hayashi US Patent 10,279,474, 2019	15	2019
Imitating object movement skills with robots—a task-level approach exploiting generalization and invariance M Gienger, M Mühlig, JJ Steil 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2010	15	2010
Learning the consequences of actions: Representing effects as feature changes M Rudolph, M Mühlig, M Gienger, HJ Böhme 2010 International Symposium on Learning and Adaptive Behavior in Robotic …, 2010	15	2010
A dynamical systems approach to adaptive sequencing of movement primitives T Luksch, M Gienger, M Mühlig, T Yoshiike ROBOTIK 2012; 7th German Conference on Robotics, 1-6, 2012	12	2012
Modeling and simulation of a multi-robot system architecture AR Sadik, C Goerick, M Muehlig 2019 International Conference on Mechatronics, Robotics and Systems …, 2019	11	2019
Context-aware modelling for multi-robot systems under uncertainty C Street, B Lacerda, M Staniaszek, M Mühlig, N Hawes International Foundation for Autonomous Agents and Multiagent Systems, 2022	8	2022
Designing interaction for multi-agent cooperative system in an office environment C Wang, S Hasler, M Mühlig, F Joublin, A Ceravola, J Deigmoeller, ... Companion of the 2021 ACM/IEEE International Conference on Human-Robot …, 2021	4	2021
Task-dependent distribution and constrained optimization of via-points for smooth robot motions CH Sung, M Mühlig, M Gienger, Y Uno 2015 IEEE International Conference on Robotics and Automation (ICRA), 3563-3569, 2015	4	2015
Right place, right time: Proactive multi-robot task allocation under spatiotemporal uncertainty C Street, B Lacerda, M Mühlig, N Hawes Journal of Artificial Intelligence Research 79, 137-171, 2024	3	2024
A knowledge-based multi-entity and cooperative system architecture M Mühlig, L Fischer, S Hasler, J Deigmöller 2020 IEEE International Conference on Human-Machine Systems (ICHMS), 1-6, 2020	3	2020

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