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Rudolf Lioutikov
Rudolf Lioutikov
TT-Professor, Intuitive Robots Lab, Karlsruhe Institute of Technology
Zweryfikowany adres z kit.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
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Probabilistic movement primitives for coordination of multiple human–robot collaborative tasks
GJ Maeda, G Neumann, M Ewerton, R Lioutikov, O Kroemer, J Peters
Autonomous Robots 41, 593-612, 2017
2412017
Learning multiple collaborative tasks with a mixture of interaction primitives
M Ewerton, G Neumann, R Lioutikov, HB Amor, J Peters, G Maeda
2015 IEEE International Conference on Robotics and Automation (ICRA), 1535-1542, 2015
1442015
Goal-Conditioned Imitation Learning using Score-based Diffusion Policies
M Reuss, M Li, X Jia, R Lioutikov
Robotics: Science and Systems, 2023
1432023
Learning interaction for collaborative tasks with probabilistic movement primitives
G Maeda, M Ewerton, R Lioutikov, HB Amor, J Peters, G Neumann
2014 IEEE-RAS International Conference on Humanoid Robots, 527-534, 2014
1312014
Model-based relative entropy stochastic search
A Abdolmaleki, R Lioutikov, JR Peters, N Lau, L Pualo Reis, G Neumann
Advances in Neural Information Processing Systems 28, 2015
1042015
Phase estimation for fast action recognition and trajectory generation in human–robot collaboration
G Maeda, M Ewerton, G Neumann, R Lioutikov, J Peters
The International Journal of Robotics Research 36 (13-14), 1579-1594, 2017
1032017
Screwnet: Category-independent articulation model estimation from depth images using screw theory
A Jain, R Lioutikov, C Chuck, S Niekum
2021 IEEE International Conference on Robotics and Automation (ICRA), 13670 …, 2021
912021
Learning movement primitive libraries through probabilistic segmentation
R Lioutikov, G Neumann, G Maeda, J Peters
The International Journal of Robotics Research 36 (8), 879-894, 2017
862017
Sample-based informationl-theoretic stochastic optimal control
R Lioutikov, A Paraschos, J Peters, G Neumann
2014 IEEE international conference on robotics and automation (ICRA), 3896-3902, 2014
772014
Self-supervised online reward shaping in sparse-reward environments
F Memarian, W Goo, R Lioutikov, S Niekum, U Topcu
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021
69*2021
Guiding trajectory optimization by demonstrated distributions
T Osa, AMG Esfahani, R Stolkin, R Lioutikov, J Peters, G Neumann
IEEE Robotics and Automation Letters 2 (2), 819-826, 2017
642017
Demonstration based trajectory optimization for generalizable robot motions
D Koert, G Maeda, R Lioutikov, G Neumann, J Peters
2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids …, 2016
582016
Prodmp: A unified perspective on dynamic and probabilistic movement primitives
G Li, Z Jin, M Volpp, F Otto, R Lioutikov, G Neumann
IEEE Robotics and Automation Letters 8 (4), 2325-2332, 2023
552023
Probabilistic segmentation applied to an assembly task
R Lioutikov, G Neumann, G Maeda, J Peters
2015 IEEE-RAS 15th international conference on humanoid robots (humanoids …, 2015
532015
Learning manipulation by sequencing motor primitives with a two-armed robot
R Lioutikov, O Kroemer, G Maeda, J Peters
Intelligent Autonomous Systems 13: Proceedings of the 13th International …, 2016
432016
Multimodal diffusion transformer: Learning versatile behavior from multimodal goals
M Reuss, ÖE Yağmurlu, F Wenzel, R Lioutikov
arXiv preprint arXiv:2407.05996, 2024
42*2024
Probabilistic prioritization of movement primitives
A Paraschos, R Lioutikov, J Peters, G Neumann
IEEE Robotics and Automation Letters 2 (4), 2294-2301, 2017
352017
Movement primitive diffusion: Learning gentle robotic manipulation of deformable objects
PM Scheikl, N Schreiber, C Haas, N Freymuth, G Neumann, R Lioutikov, ...
IEEE Robotics and Automation Letters, 2024
302024
Distributional depth-based estimation of object articulation models
A Jain, S Giguere, R Lioutikov, S Niekum
Conference on Robot Learning, 1611-1621, 2022
252022
Towards diverse behaviors: A benchmark for imitation learning with human demonstrations
X Jia, D Blessing, X Jiang, M Reuss, A Donat, R Lioutikov, G Neumann
arXiv preprint arXiv:2402.14606, 2024
242024
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