An algorithmic perspective on imitation learning T Osa, J Pajarinen, G Neumann, JA Bagnell, P Abbeel, J Peters Foundations and Trends® in Robotics 7 (1-2), 1-179, 2018 | 877 | 2018 |
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 | 133 | 2023 |
Reducing overestimation bias in multi-agent domains using double centralized critics J Ackermann, V Gabler, T Osa, M Sugiyama arXiv preprint arXiv:1910.01465, 2019 | 115 | 2019 |
Online Trajectory Planning and Force Control for Automation of Surgical Tasks T Osa, N Sugita, M Mitsuishi IEEE Transactions on Automation Science and Enigneering 15 (2), 675-691, 2018 | 92 | 2018 |
Automation of tissue piercing using circular needles and vision guidance for computer aided laparoscopic surgery C Staub, T Osa, A Knoll, R Bauernschmitt 2010 IEEE International Conference on Robotics and Automation, 4585-4590, 2010 | 79 | 2010 |
Framework of automatic robot surgery system using visual servoing T Osa, C Staub, A Knoll 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2010 | 77 | 2010 |
Analysis and estimation of cutting-temperature distribution during end milling in relation to orthopedic surgery N Sugita, T Osa, M Mitsuishi Medical engineering & physics 31 (1), 101-107, 2009 | 73 | 2009 |
A new cutting method for bone based on its crack propagation characteristics N Sugita, T Osa, R Aoki, M Mitsuishi CIRP annals 58 (1), 113-118, 2009 | 69 | 2009 |
Active Incremental Learning of Robot Movement Primitives G Maeda, M Ewerton, T Osa, B Busch, J Peters Conference on Robot Learning, 2017 | 66 | 2017 |
Guiding Trajectory Optimization by Demonstrated Distributions T Osa, AM Ghalamzan E., R Stolkin, R Lioutikov, J Peters, G Neumann IEEE Robotics and Automation Letters 2 (2), 819-826, 2017 | 61 | 2017 |
Multimodal trajectory optimization for motion planning T Osa The International Journal of Robotics Research 39 (8), 983-1001, 2020 | 60 | 2020 |
A learning-based shared control architecture for interactive task execution F Abi-Farraj, T Osa, NPJ Peters, G Neumann, PR Giordano 2017 IEEE international conference on robotics and automation (ICRA), 329-335, 2017 | 60 | 2017 |
Online Trajectory Planning in Dynamic Environments for Surgical Task Automation. T Osa, N Sugita, M Mitsuishi Robotics: Science and Systems, 1-9, 2014 | 51 | 2014 |
Hand-held bone cutting tool with autonomous penetration detection for spinal surgery T Osa, CF Abawi, N Sugita, H Chikuda, S Sugita, T Tanaka, H Oshima, ... IEEE/ASME Transactions on Mechatronics 20 (6), 3018-3027, 2015 | 42 | 2015 |
Hierarchical Reinforcement Learning via Advantage-Weighted Information Maximization T Osa, V Tangkaratt, M Sugiyama The Seventh International Conference on Learning Representations (ICLR 2019), 2019 | 37 | 2019 |
Trajectory planning under different initial conditions for surgical task automation by learning from demonstration T Osa, K Harada, N Sugita, M Mitsuishi 2014 IEEE International Conference on Robotics and Automation (ICRA), 6507-6513, 2014 | 37 | 2014 |
Discovering diverse solutions in deep reinforcement learning by maximizing state–action-based mutual information T Osa, V Tangkaratt, M Sugiyama Neural Networks 152, 90-104, 2022 | 32* | 2022 |
Hierarchical reinforcement learning of multiple grasping strategies with human instructions T Osa, J Peters, G Neumann Advanced Robotics, 2018 | 30 | 2018 |
Sample and feedback efficient hierarchical reinforcement learning from human preferences R Pinsler, R Akrour, T Osa, J Peters, G Neumann 2018 IEEE international conference on robotics and automation (ICRA), 596-601, 2018 | 27 | 2018 |
Experiments with Hierarchical Reinforcement Learning of Multiple Grasping Policies T Osa, J Peters, G Neumann Proceedings of the International Symposium on Experimental Robotics (ISER), 2016 | 22 | 2016 |