Reinforcement learning for robotic assembly using non-diagonal stiffness matrix M Oikawa, T Kusakabe, K Kutsuzawa, S Sakaino, T Tsuji IEEE Robotics and Automation Letters 6 (2), 2737-2744, 2021 | 39 | 2021 |
A survey of sim-to-real transfer techniques applied to reinforcement learning for bioinspired robots W Zhu, X Guo, D Owaki, K Kutsuzawa, M Hayashibe IEEE Transactions on Neural Networks and Learning Systems 34 (7), 3444-3459, 2021 | 31 | 2021 |
Optimized trajectory generation based on model predictive control for turning over pancakes T Tsuji, K Kutsuzawa, S Sakaino IEEJ Journal of Industry Applications 7 (1), 22-28, 2018 | 16 | 2018 |
Sequence-to-sequence model for trajectory planning of nonprehensile manipulation including contact model K Kutsuzawa, S Sakaino, T Tsuji IEEE Robotics and Automation Letters 3 (4), 3606-3613, 2018 | 15 | 2018 |
Spiking neural network discovers energy-efficient hexapod motion in deep reinforcement learning K Naya, K Kutsuzawa, D Owaki, M Hayashibe IEEE Access 9, 150345-150354, 2021 | 13 | 2021 |
Motor synergy generalization framework for new targets in multi-planar and multi-directional reaching task K Kutsuzawa, M Hayashibe Royal Society Open Science 9 (5), 211721, 2022 | 11 | 2022 |
Assembly robots with optimized control stiffness through reinforcement learning M Oikawa, K Kutsuzawa, S Sakaino, T Tsuji arXiv preprint arXiv:2002.12207, 2020 | 9 | 2020 |
Trajectory adjustment for nonprehensile manipulation using latent space of trained sequence-to-sequence model K Kutsuzawa, S Sakaino, T Tsuji Advanced Robotics 33 (21), 1144-1154, 2019 | 8 | 2019 |
Individual deformability compensation of soft hydraulic actuators through iterative learning-based neural network T Sugiyama, K Kutsuzawa, D Owaki, M Hayashibe Bioinspiration & Biomimetics 16 (5), 056016, 2021 | 7 | 2021 |
Motion planning with success judgement model based on learning from demonstration D Furuta, K Kutsuzawa, S Sakaino, T Tsuji IEEE Access 8, 73142-73150, 2020 | 7 | 2020 |
A control system for a tool use robot: Drawing a circle by educing functions of a compass K Kutsuzawa, S Sakaino, T Tsuji Journal of Robotics and Mechatronics 29 (2), 395-405, 2017 | 7 | 2017 |
Sequence-to-sequence models for trajectory deformation of dynamic manipulation K Kutsuzawa, S Sakaino, T Tsuji IECON 2017-43rd Annual Conference of the IEEE Industrial Electronics Society …, 2017 | 6 | 2017 |
Multimodal bipedal locomotion generation with passive dynamics via deep reinforcement learning S Koseki, K Kutsuzawa, D Owaki, M Hayashibe Frontiers in Neurorobotics 16, 1054239, 2023 | 5 | 2023 |
Admittance control based on a stiffness ellipse for rapid trajectory deformation M Oikawa, K Kutsuzawa, S Sakaino, T Tsuji 2020 IEEE 16th International Workshop on Advanced Motion Control (AMC), 23-28, 2020 | 5 | 2020 |
Transhumeral arm reaching motion prediction through deep reinforcement learning-based synthetic motion cloning MH Ahmed, K Kutsuzawa, M Hayashibe Biomimetics 8 (4), 367, 2023 | 4 | 2023 |
Quantifying motor and cognitive function of the upper limb using mixed reality smartglasses K Tada, K Kutsuzawa, D Owaki, M Hayashibe 2022 44th Annual International Conference of the IEEE Engineering in …, 2022 | 4 | 2022 |
Simultaneous estimation of contact position and tool shape using an unscented particle filter K Kutsuzawa, S Sakaino, T Tsuji IEEJ Journal of Industry Applications 9 (5), 505-514, 2020 | 4 | 2020 |
Integrated Quantitative Evaluation of Spatial Cognition and Motor Function with HoloLens Mixed Reality K Tada, Y Sorimachi, K Kutsuzawa, D Owaki, M Hayashibe Sensors 24 (2), 528, 2024 | 3 | 2024 |
Game-based Evaluation of Whole-body Movement Functions with CoM Stability and Motion Smoothness M Kojima, K Kutsuzawa, D Owaki, M Hayashibe 2022 44th Annual International Conference of the IEEE Engineering in …, 2022 | 3 | 2022 |
Motion generation considering situation with conditional generative adversarial networks for throwing robots K Kutsuzawa, H Kusano, A Kume, S Yamaguchi arXiv preprint arXiv:1910.03253, 2019 | 3 | 2019 |