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2020 – today
- 2024
[j58]Chang Liu, Satoshi Yagi, Satoshi Yamamori, Jun Morimoto:
Joint-Aware Transformer: An Inter-Joint Correlation Encoding Transformer for Short-Term 3D Human Motion Prediction. IEEE Access 12: 156683-156693 (2024)- [j57]Matija Mavsar
, Jun Morimoto, Ales Ude:
GAN-Based Semi-Supervised Training of LSTM Nets for Intention Recognition in Cooperative Tasks. IEEE Robotics Autom. Lett. 9(1): 263-270 (2024) - [j56]Matija Mavsar, Barry Ridge, Rok Pahic, Jun Morimoto, Ales Ude:
Simulation-Aided Handover Prediction From Video Using Recurrent Image-to-Motion Networks. IEEE Trans. Neural Networks Learn. Syst. 35(1): 494-506 (2024) - [i12]Satoshi Yagi, Mitsunori Tada, Eiji Uchibe, Suguru Kanoga, Takamitsu Matsubara, Jun Morimoto:
Unsupervised Neural Motion Retargeting for Humanoid Teleoperation. CoRR abs/2406.00727 (2024) - [i11]Satoshi Yamamori, Jun Morimoto:
Phase-Amplitude Reduction-Based Imitation Learning. CoRR abs/2406.03735 (2024) - [i10]Koji Ishihara, Hiroaki Gomi, Jun Morimoto:
Hierarchical Learning Framework for Whole-Body Model Predictive Control of a Real Humanoid Robot. CoRR abs/2409.08488 (2024) - [i9]Mitsuki Morita, Satoshi Yamamori, Satoshi Yagi, Norikazu Sugimoto, Jun Morimoto:
Goal-Conditioned Terminal Value Estimation for Real-time and Multi-task Model Predictive Control. CoRR abs/2410.04929 (2024) - 2023
- [j55]Sunhwi Kang, Koji Ishihara, Norikazu Sugimoto, Jun Morimoto:
Curriculum-based humanoid robot identification using large-scale human motion database. Frontiers Robotics AI 10 (2023) - [j54]Takumi Hachimine, Jun Morimoto, Takamitsu Matsubara:
Learning to Shape by Grinding: Cutting-Surface-Aware Model-Based Reinforcement Learning. IEEE Robotics Autom. Lett. 8(10): 6235-6242 (2023) - [c90]Takahide Ito, Jun-ichiro Furukawa, Qi An, Jun Morimoto, Yuichi Nakamura:
Muscle Synergy Analysis Under Fast Sit-to-stand Assist : A Preliminary Study. AHs 2023: 320-322 - [i8]Takumi Hachimine, Jun Morimoto, Takamitsu Matsubara:
Learning to Shape by Grinding: Cutting-surface-aware Model-based Reinforcement Learning. CoRR abs/2308.02150 (2023) - [i7]Satoshi Yamamori, Jun Morimoto:
A Policy Adaptation Method for Implicit Multitask Reinforcement Learning Problems. CoRR abs/2308.16471 (2023) - 2022
- [j53]Takeshi D. Itoh, Koji Ishihara, Jun Morimoto:
Implicit Contact Dynamics Modeling With Explicit Inertia Matrix Representation for Real-Time, Model-Based Control in Physical Environment. Neural Comput. 34(2): 360-377 (2022) - [j52]Yutaka Matsuo, Yann LeCun, Maneesh Sahani, Doina Precup, David Silver, Masashi Sugiyama, Eiji Uchibe, Jun Morimoto:
Deep learning, reinforcement learning, and world models. Neural Networks 152: 267-275 (2022) - [j51]Jun-ichiro Furukawa, Shotaro Okajima, Qi An, Yuichi Nakamura, Jun Morimoto:
Selective Assist Strategy by Using Lightweight Carbon Frame Exoskeleton Robot. IEEE Robotics Autom. Lett. 7(2): 3890-3897 (2022) - [j50]Tomoya Yamanokuchi, Yuhwan Kwon, Yoshihisa Tsurumine, Eiji Uchibe, Jun Morimoto, Takamitsu Matsubara:
Randomized-to-Canonical Model Predictive Control for Real-World Visual Robotic Manipulation. IEEE Robotics Autom. Lett. 7(4): 8964-8971 (2022) - [c89]Yamato Kuroda, Qi An, Hiroshi Yamakawa, Shingo Shimoda, Jun-ichiro Furukawa, Jun Morimoto, Yuichi Nakamura, Ryo Kurazume:
Development of a Chair to Support Human Standing Motion -Seat movement mechanism using zip chain actuator-. SII 2022: 555-560 - [i6]Tomoya Yamanokuchi, Yuhwan Kwon, Yoshihisa Tsurumine, Eiji Uchibe, Jun Morimoto, Takamitsu Matsubara:
Randomized-to-Canonical Model Predictive Control for Real-world Visual Robotic Manipulation. CoRR abs/2207.01840 (2022) - 2021
- [j49]Masashi Hamaya, Takamitsu Matsubara, Tatsuya Teramae, Tomoyuki Noda, Jun Morimoto:
Design of physical user-robot interactions for model identification of soft actuators on exoskeleton robots. Int. J. Robotics Res. 40(1) (2021) - [j48]Tom Macpherson, Masayuki Matsumoto, Hiroaki Gomi, Jun Morimoto, Eiji Uchibe, Takatoshi Hikida:
Parallel and hierarchical neural mechanisms for adaptive and predictive behavioral control. Neural Networks 144: 507-521 (2021) - [j47]Jun-ichiro Furukawa, Jun Morimoto:
Composing an Assistive Control Strategy Based on Linear Bellman Combination From Estimated User's Motor Goal. IEEE Robotics Autom. Lett. 6(2): 1051-1058 (2021) - [j46]Jun-ichiro Furukawa, Shinya Chiyohara, Tatsuya Teramae, Asuka Takai, Jun Morimoto:
A Collaborative Filtering Approach Toward Plug-and-Play Myoelectric Robot Control. IEEE Trans. Hum. Mach. Syst. 51(5): 514-523 (2021) - [c88]Koji Ishihara, Jun Morimoto:
Computationally Affordable Hierarchical Framework for Humanoid Robot Control. IROS 2021: 7349-7356 - 2020
- [j45]Rok Pahic, Barry Ridge, Andrej Gams, Jun Morimoto, Ales Ude:
Training of deep neural networks for the generation of dynamic movement primitives. Neural Networks 127: 121-131 (2020) - [j44]Guilherme Maeda, Okan Koc, Jun Morimoto:
Phase portraits as movement primitives for fast humanoid robot control. Neural Networks 129: 109-122 (2020) - [j43]Koji Ishihara, Takeshi D. Itoh, Jun Morimoto:
Full-Body Optimal Control Toward Versatile and Agile Behaviors in a Humanoid Robot. IEEE Robotics Autom. Lett. 5(1): 119-126 (2020) - [j42]Tatsuya Teramae, Takamitsu Matsubara, Tomoyuki Noda, Jun Morimoto:
Quaternion-Based Trajectory Optimization of Human Postures for Inducing Target Muscle Activation Patterns. IEEE Robotics Autom. Lett. 5(4): 6607-6614 (2020)
2010 – 2019
- 2019
- [j41]Tadej Petric, Luka Peternel, Jun Morimoto, Jan Babic:
Assistive Arm-Exoskeleton Control Based on Human Muscular Manipulability. Frontiers Neurorobotics 13: 30 (2019) - [j40]Barkan Ugurlu, Paolo Forni, Corinne Doppmann, Emre Sariyildiz, Jun Morimoto:
Stable Control of Force, Position, and Stiffness for Robot Joints Powered via Pneumatic Muscles. IEEE Trans. Ind. Informatics 15(12): 6270-6279 (2019) - [c87]Masashi Hamaya, Takamitsu Matsubara, Jun-ichiro Furukawa, Yuting Sun, Satoshi Yagi, Tatsuya Teramae, Tomoyuki Noda, Jun Morimoto:
Exploiting Human and Robot Muscle Synergies for Human-in-the-loop Optimization of EMG-based Assistive Strategies. ICRA 2019: 549-555 - [c86]Barry Ridge, Rok Pahic, Ales Ude, Jun Morimoto:
Learning to Write Anywhere with Spatial Transformer Image-to-Motion Encoder-Decoder Networks. ICRA 2019: 2111-2117 - [c85]Barry Ridge, Rok Pahic, Ales Ude, Jun Morimoto:
Convolutional Encoder-Decoder Networks for Robust Image-to-Motion Prediction. RAAD 2019: 514-523 - [p1]Kenichi Takasaki, Fumio Liu, Miho Ogura, Kohei Okuyama, Michiyuki Kawakami, Katsuhiko Mizuno, Shoko Kasuga, Tomoyuki Noda, Jun Morimoto, Meigen Liu, Junichi Ushiba:
Targeted Up-Conditioning of Contralesional Corticospinal Pathways Promotes Motor Recovery in Poststroke Patients with Severe Chronic Hemiplegia. Brain-Computer Interface Research (7) 2019: 75-82 - [i5]Jun-ichiro Furukawa, Jun Morimoto:
An Optimal Assistive Control Strategy based on User's Motor Goal Estimation. CoRR abs/1909.02288 (2019) - [i4]Guilherme Maeda, Okan Koc, Jun Morimoto:
Phase Portraits as Movement Primitives for Fast Humanoid Robot Control. CoRR abs/1912.03535 (2019) - 2018
- [j39]Tatsuya Teramae, Koji Ishihara, Jan Babic, Jun Morimoto, Erhan Öztop:
Human-In-The-Loop Control and Task Learning for Pneumatically Actuated Muscle Based Robots. Frontiers Neurorobotics 12: 71 (2018) - [j38]Koji Ishihara, Jun Morimoto:
An optimal control strategy for hybrid actuator systems: Application to an artificial muscle with electric motor assist. Neural Networks 99: 92-100 (2018) - [j37]Tatsuya Teramae, Tomoyuki Noda, Jun Morimoto:
EMG-Based Model Predictive Control for Physical Human-Robot Interaction: Application for Assist-As-Needed Control. IEEE Robotics Autom. Lett. 3(1): 210-217 (2018) - [j36]Timotej Gaspar, Bojan Nemec, Jun Morimoto, Ales Ude:
Skill learning and action recognition by arc-length dynamic movement primitives. Robotics Auton. Syst. 100: 225-235 (2018) - [c84]Daniel F. N. Gordon, Takamitsu Matsubara, Tomoyuki Noda, Tatsuya Teramae, Jun Morimoto, Sethu Vijayakumar:
Bayesian Optimisation of Exoskeleton Design Parameters. BioRob 2018: 653-658 - [c83]Guilherme Maeda, Okan Koc, Jun Morimoto:
Reinforcement Learning of Phase Oscillators for Fast Adaptation to Moving Targets. CoRL 2018: 630-640 - [c82]Sara Hamdan, Erhan Öztop, Jun-ichiro Furukawa, Jun Morimoto, Barkan Ugurlu:
Shoulder Glenohumeral Elevation Estimation based on Upper Arm Orientation. EMBC 2018: 1481-1484 - [c81]Rok Pahic, Andrej Gams, Ales Ude, Jun Morimoto:
Deep Encoder-Decoder Networks for Mapping Raw Images to Dynamic Movement Primitives. ICRA 2018: 1-6 - [c80]Tomoyuki Noda, Asuka Takai, Tatsuya Teramae, Eiko Hirookai, Kimitaka Hase, Jun Morimoto:
Robotizing Double-Bar Ankle-Foot Orthosis. ICRA 2018: 2782-2787 - [c79]Asuka Takai, Diletta Rivela, Giuseppe Lisi, Tomoyuki Noda, Tatsuya Teramae, Hiroshi Imamizu, Jun Morimoto:
Investigation on the Neural Correlates of Haptic Training. SMC 2018: 519-523 - [c78]Miho Ogura, Jun-ichiro Furukawa, Tatsuya Teramae, Tomoyuki Noda, Kohei Okuyama, Michiyuki Kawakami, Meigen Liu, Jun Morimoto:
Development of Shoulder Exoskeleton Toward BMI Triggered Rehabilitation Robot Therapy. SMC 2018: 1105-1109 - 2017
- [j35]Masashi Hamaya, Takamitsu Matsubara, Tomoyuki Noda, Tatsuya Teramae, Jun Morimoto:
Learning assistive strategies for exoskeleton robots from user-robot physical interaction. Pattern Recognit. Lett. 99: 67-76 (2017) - [j34]Jun-ichiro Furukawa, Tomoyuki Noda, Tatsuya Teramae, Jun Morimoto:
Human Movement Modeling to Detect Biosignal Sensor Failures for Myoelectric Assistive Robot Control. IEEE Trans. Robotics 33(4): 846-857 (2017) - [c77]Jun-ichiro Furukawa, Asuka Takai, Jun Morimoto:
Database-driven approach for Biosignal-based robot control with collaborative filtering. Humanoids 2017: 606-611 - [c76]Masashi Hamaya, Takamitsu Matsubara, Tomoyuki Noda, Tatsuya Teramae, Jun Morimoto:
Learning task-parametrized assistive strategies for exoskeleton robots by multi-task reinforcement learning. ICRA 2017: 5907-5912 - [c75]Rok Goljat, Jan Babic, Tadej Petric, Luka Peternel, Jun Morimoto:
Power-augmentation control approach for arm exoskeleton based on human muscular manipulability. ICRA 2017: 5929-5934 - [c74]Masashi Hamaya, Takamitsu Matsubara, Tomoyuki Noda, Tatsuya Teramae, Jun Morimoto:
User-robot collaborative excitation for PAM model identification in exoskeleton robots. IROS 2017: 3063-3068 - [r2]Jan Peters, Russ Tedrake, Nick Roy, Jun Morimoto:
Robot Learning. Encyclopedia of Machine Learning and Data Mining 2017: 1106-1109 - 2016
- [j33]Voot Tangkaratt, Jun Morimoto, Masashi Sugiyama:
Model-based reinforcement learning with dimension reduction. Neural Networks 84: 1-16 (2016) - [j32]Norikazu Sugimoto, Voot Tangkaratt, Thijs Wensveen, Tingting Zhao, Masashi Sugiyama, Jun Morimoto:
Trial and Error: Using Previous Experiences as Simulation Models in Humanoid Motor Learning. IEEE Robotics Autom. Mag. 23(1): 96-105 (2016) - [j31]Andrej Gams, Tadej Petric, Martin Do, Bojan Nemec, Jun Morimoto, Tamim Asfour, Ales Ude:
Adaptation and coaching of periodic motion primitives through physical and visual interaction. Robotics Auton. Syst. 75: 340-351 (2016) - [j30]Jun-ichiro Furukawa, Tomoyuki Noda, Tatsuya Teramae, Jun Morimoto:
An EMG-Driven Weight Support System With Pneumatic Artificial Muscles. IEEE Syst. J. 10(3): 1026-1034 (2016) - [c73]Giuseppe Lisi, Masashi Hamaya, Tomoyuki Noda, Jun Morimoto:
Dry-wireless EEG and asynchronous adaptive feature extraction towards a plug-and-play co-adaptive brain robot interface. ICRA 2016: 959-966 - [c72]Masashi Hamaya, Takamitsu Matsubara, Tomoyuki Noda, Tatsuya Teramae, Jun Morimoto:
Learning assistive strategies from a few user-robot interactions: Model-based reinforcement learning approach. ICRA 2016: 3346-3351 - [c71]Ales Ude, Rok Vuga, Bojan Nemec, Jun Morimoto:
Trajectory representation by nonlinear scaling of dynamic movement primitives. IROS 2016: 4728-4735 - 2015
- [j29]Jun-ichiro Furukawa, Tomoyuki Noda, Tatsuya Teramae, Jun Morimoto:
Fault tolerant approach for biosignal-based robot control. Adv. Robotics 29(7): 505-514 (2015) - [j28]Takamitsu Matsubara, Akimasa Uchikata, Jun Morimoto:
Spatiotemporal synchronization of biped walking patterns with multiple external inputs by style-phase adaptation. Biol. Cybern. 109(6): 597-610 (2015) - [c70]Koji Ishihara, Jun Morimoto:
Real-time Model Predictive Control with two-step optimization based on singularly perturbed system. Humanoids 2015: 173-180 - [c69]Luka Peternel, Barkan Ugurlu, Jan Babic, Jun Morimoto:
Assessments on the improved modelling for pneumatic artificial muscle actuators. ICAR 2015: 34-39 - [c68]Jessica Beltran Ullauri, Luka Peternel, Barkan Ugurlu, Yoji Yamada, Jun Morimoto:
On the EMG-based torque estimation for humans coupled with a force-controlled elbow exoskeleton. ICAR 2015: 302-307 - [c67]Jun-ichiro Furukawa, Tomoyuki Noda, Tatsuya Teramae, Jun Morimoto:
Estimating joint movements from observed EMG signals with multiple electrodes under sensor failure situations toward safe assistive robot control. ICRA 2015: 4985-4991 - [c66]Corinne Doppmann, Barkan Ugurlu, Masashi Hamaya, Tatsuya Teramae, Tomoyuki Noda, Jun Morimoto:
Towards balance recovery control for lower body exoskeleton robots with Variable Stiffness Actuators: Spring-loaded flywheel model. ICRA 2015: 5551-5556 - [c65]Barkan Ugurlu, Paolo Forni, Corinne Doppmann, Jun Morimoto:
Torque and variable stiffness control for antagonistically driven pneumatic muscle actuators via a stable force feedback controller. IROS 2015: 1633-1639 - [c64]Andrej Gams, Ales Ude, Jun Morimoto:
Accelerating synchronization of movement primitives: Dual-arm discrete-periodic motion of a humanoid robot. IROS 2015: 2754-2760 - [c63]Yoshihiro Nakata, Tomoyuki Noda, Jun Morimoto, Hiroshi Ishiguro:
Development of a pneumatic-electromagnetic hybrid linear actuator with an integrated structure. IROS 2015: 6238-6243 - [c62]Yuka Ariki, Tetsunari Inamura, Shiro Ikeda, Jun Morimoto:
Sparsely extracting stored movements to construct interfaces for humanoid end-effector control. ROBIO 2015: 1816-1821 - 2014
- [j27]Voot Tangkaratt, Syogo Mori, Tingting Zhao, Jun Morimoto, Masashi Sugiyama:
Model-based policy gradients with parameter-based exploration by least-squares conditional density estimation. Neural Networks 57: 128-140 (2014) - [c61]Takamitsu Matsubara, Daisuke Uto, Tomoyuki Noda, Tatsuya Teramae, Jun Morimoto:
Style-phase adaptation of human and humanoid biped walking patterns in real systems. Humanoids 2014: 128-133 - [c60]Yuka Ariki, Tetsunari Inamura, Jun Morimoto:
Observing human movements to construct a humanoid interface. Humanoids 2014: 342-347 - [c59]Norikazu Sugimoto, Voot Tangkaratt, Thijs Wensveen, Tingting Zhao, Masashi Sugiyama, Jun Morimoto:
Efficient reuse of previous experiences in humanoid motor learning. Humanoids 2014: 554-559 - [c58]Ales Ude, Bojan Nemec, Tadej Petric, Jun Morimoto:
Orientation in Cartesian space dynamic movement primitives. ICRA 2014: 2997-3004 - [c57]Tadej Petric, Andrej Gams, Leon Zlajpah, Ales Ude, Jun Morimoto:
Online approach for altering robot behaviors based on human in the loop coaching gestures. ICRA 2014: 4770-4776 - [c56]Tatsuya Teramae, Tomoyuki Noda, Jun Morimoto:
Optimal control approach for pneumatic artificial muscle with using pressure-force conversion model. ICRA 2014: 4792-4797 - [c55]Tomoyuki Noda, Tatsuya Teramae, Barkan Ugurlu, Jun Morimoto:
Development of an upper limb exoskeleton powered via pneumatic electric hybrid actuators with bowden cable. IROS 2014: 3573-3578 - [i3]Norikazu Sugimoto, Voot Tangkaratt, Thijs Wensveen, Tingting Zhao, Masashi Sugiyama, Jun Morimoto:
Efficient Reuse of Previous Experiences to Improve Policies in Real Environment. CoRR abs/1405.2406 (2014) - 2013
- [j26]David Schiebener, Jun Morimoto, Tamim Asfour, Ales Ude:
Integrating visual perception and manipulation for autonomous learning of object representations. Adapt. Behav. 21(5): 328-345 (2013) - [j25]Poramate Manoonpong, Christoph Kolodziejski, Florentin Wörgötter, Jun Morimoto:
Combining Correlation-Based and Reward-Based Learning in Neural Control for Policy Improvement. Adv. Complex Syst. 16(2-3) (2013) - [j24]Tingting Zhao, Hirotaka Hachiya, Voot Tangkaratt, Jun Morimoto, Masashi Sugiyama:
Efficient Sample Reuse in Policy Gradients with Parameter-Based Exploration. Neural Comput. 25(6): 1512-1547 (2013) - [j23]Yuka Ariki, Sang-Ho Hyon, Jun Morimoto:
Extraction of primitive representation from captured human movements and measured ground reaction force to generate physically consistent imitated behaviors. Neural Networks 40: 32-43 (2013) - [j22]Takamitsu Matsubara, Jun Morimoto:
Bilinear Modeling of EMG Signals to Extract User-Independent Features for Multiuser Myoelectric Interface. IEEE Trans. Biomed. Eng. 60(8): 2205-2213 (2013) - [c54]Norikazu Sugimoto, Jun Morimoto:
Trajectory-model-based reinforcement learning: Application to bimanual humanoid motor learning with a closed-chain constraint. Humanoids 2013: 429-434 - [c53]Karim Bouyarmane, Joris Vaillant, Norikazu Sugimoto, François Keith, Jun-ichiro Furukawa, Jun Morimoto:
BCI Control of Whole-Body Simulated Humanoid by Combining Motor Imagery Detection and Autonomous Motion Planning. ICONIP (1) 2013: 310-318 - [c52]Norikazu Sugimoto, Jun Morimoto:
Off-line path integral reinforcement learning using stochastic robot dynamics approximated by sparse pseudo-input Gaussian processes: Application to humanoid robot motor learning in the real environment. ICRA 2013: 1311-1316 - [c51]Hiromichi Suetani, Jun Morimoto:
Canonical correlation analysis for muscle synergies organized by sensory-motor interactions in musculoskeletal arm movements. ICRA 2013: 2606-2611 - [c50]Tomoyuki Noda, Jun-ichiro Furukawa, Tatsuya Teramae, Sang-Ho Hyon, Jun Morimoto:
An electromyogram based force control coordinated in assistive interaction. ICRA 2013: 2657-2662 - [c49]Rok Vuga, Matjaz Ogrinc, Andrej Gams, Tadej Petric, Norikazu Sugimoto, Ales Ude, Jun Morimoto:
Motion capture and reinforcement learning of dynamically stable humanoid movement primitives. ICRA 2013: 5284-5290 - [c48]Sang-Ho Hyon, Takuya Hayashi, Atsutoshi Yagi, Tomoyuki Noda, Jun Morimoto:
Design of hybrid drive exoskeleton robot XoR2. IROS 2013: 4642-4648 - [c47]Tatsuya Teramae, Tomoyuki Noda, Sang-Ho Hyon, Jun Morimoto:
Modeling and control of a Pneumatic-Electric hybrid system. IROS 2013: 4887-4892 - [c46]Sakyasingha Dasgupta, Florentin Wörgötter, Jun Morimoto, Poramate Manoonpong:
Neural Combinatorial Learning of Goal-Directed Behavior with Reservoir Critic and Reward Modulated Hebbian Plasticity. SMC 2013: 993-1000 - [i2]Tingting Zhao, Hirotaka Hachiya, Voot Tangkaratt, Jun Morimoto, Masashi Sugiyama:
Efficient Sample Reuse in Policy Gradients with Parameter-based Exploration. CoRR abs/1301.3966 (2013) - [i1]Syogo Mori, Voot Tangkaratt, Tingting Zhao, Jun Morimoto, Masashi Sugiyama:
Model-Based Policy Gradients with Parameter-Based Exploration by Least-Squares Conditional Density Estimation. CoRR abs/1307.5118 (2013) - 2012
- [j21]Takamitsu Matsubara, Sang-Ho Hyon, Jun Morimoto:
Real-time stylistic prediction for whole-body human motions. Neural Networks 25: 191-199 (2012) - [j20]Norikazu Sugimoto, Jun Morimoto, Sang-Ho Hyon, Mitsuo Kawato:
The eMOSAIC model for humanoid robot control. Neural Networks 29: 8-19 (2012) - [j19]Denis Forte, Andrej Gams, Jun Morimoto, Ales Ude:
On-line motion synthesis and adaptation using a trajectory database. Robotics Auton. Syst. 60(10): 1327-1339 (2012) - [c45]Tomoyuki Noda, Norikazu Sugimoto, Jun-ichiro Furukawa, Masa-aki Sato, Sang-Ho Hyon, Jun Morimoto:
Brain-controlled exoskeleton robot for BMI rehabilitation. Humanoids 2012: 21-27 - [c44]Hiromichi Suetani, Aiko M. Ideta, Jun Morimoto:
Using basin ruins and co-moving low-dimensional latent coordinates for dynamic programming of biped walkers on roughing ground. ICRA 2012: 517-523 - [c43]Takamitsu Matsubara, Akimasa Uchikata, Jun Morimoto:
Spatio-temporal synchronization of periodic movements by style-phase adaptation: Application to biped walking. ICRA 2012: 524-530 - [c42]Ales Ude, David Schiebener, Norikazu Sugimoto, Jun Morimoto:
Integrating surface-based hypotheses and manipulation for autonomous segmentation and learning of object representations. ICRA 2012: 1709-1715 - [c41]Jun Morimoto, Tomoyuki Noda, Sang-Ho Hyon:
Extraction of latent kinematic relationships between human users and assistive robots. ICRA 2012: 3909-3915 - [c40]Takamitsu Matsubara, Akimasa Uchikata, Jun Morimoto:
Full-body exoskeleton robot control for walking assistance by style-phase adaptive pattern generation. IROS 2012: 3914-3920 - 2011
- [j18]Takamitsu Matsubara, Sang-Ho Hyon, Jun Morimoto:
Learning parametric dynamic movement primitives from multiple demonstrations. Neural Networks 24(5): 493-500 (2011) - [c39]Norikazu Sugimoto, Jun Morimoto:
Phase-dependent trajectory optimization for CPG-based biped walking using path integral reinforcement learning. Humanoids 2011: 255-260 - [c38]Takamitsu Matsubara, Tomoyuki Noda, Sang-Ho Hyon, Jun Morimoto:
An optimal control approach for hybrid actuator system. Humanoids 2011: 300-305 - [c37]David Schiebener, Ales Ude, Jun Morimoto, Tamim Asfour, Rüdiger Dillmann:
Segmentation and learning of unknown objects through physical interaction. Humanoids 2011: 500-506 - [c36]Hiromichi Suetani, Aiko M. Ideta, Jun Morimoto:
Nonlinear structure of escape-times to falls for a passive dynamic walker on an irregular slope: Anomaly detection using multi-class support vector machine and latent state extraction by canonical correlation analysis. IROS 2011: 2715-2722 - [c35]Norikazu Sugimoto, Jun Morimoto:
Switching multiple LQG controllers based on Bellman's optimality principle: Using full-state feedback to control a humanoid robot. IROS 2011: 3185-3191 - [c34]Sang-Ho Hyon, Jun Morimoto, Takamitsu Matsubara, Tomoyuki Noda, Mitsuo Kawato:
XoR: Hybrid drive exoskeleton robot that can balance. IROS 2011: 3975-3981 - [c33]Takamitsu Matsubara, Sang-Ho Hyon, Jun Morimoto:
Learning and adaptation of a Stylistic Myoelectric Interface: EMG-based robotic control with individual user differences. ROBIO 2011: 390-395 - 2010
- [j17]Ales Ude, Andrej Gams, Tamim Asfour, Jun Morimoto:
Task-Specific Generalization of Discrete and Periodic Dynamic Movement Primitives. IEEE Trans. Robotics 26(5): 800-815 (2010) - [c32]Takamitsu Matsubara, Sang-Ho Hyon, Jun Morimoto:
Learning Parametric Dynamic Movement Primitives from Multiple Demonstrations. ICONIP (1) 2010: 347-354 - [c31]Poramate Manoonpong, Florentin Wörgötter, Jun Morimoto:
Extraction of Reward-Related Feature Space Using Correlation-Based and Reward-Based Learning Methods. ICONIP (1) 2010: 414-421 - [c30]Sang-Ho Hyon, Jun Morimoto, Mitsuo Kawato:
From compliant balancing to dynamic walking on humanoid robot: Integration of CNS and CPG. ICRA 2010: 1084-1085 - [c29]Takamitsu Matsubara, Sang-Ho Hyon, Jun Morimoto:
Learning Stylistic Dynamic Movement Primitives from multiple demonstrations. IROS 2010: 1277-1283 - [c28]Norikazu Sugimoto, Jun Morimoto, Sang-Ho Hyon, Mitsuo Kawato:
eMOSAIC Model for Humanoid Robot Control. SAB 2010: 447-457 - [c27]Takamitsu Matsubara, Tetsuro Morimura, Jun Morimoto:
Adaptive Step-size Policy Gradients with Average Reward Metric. ACML 2010: 285-298 - [r1]Jan Peters, Russ Tedrake, Nicholas Roy, Jun Morimoto:
Robot Learning. Encyclopedia of Machine Learning 2010: 865-869
2000 – 2009
- 2009
- [j16]Jun Morimoto, Christopher G. Atkeson:
Nonparametric representation of an approximated Poincaré map for learning biped locomotion. Auton. Robots 27(2): 131-144 (2009) - [j15]Jan Peters, Jun Morimoto, Russ Tedrake, Nicholas Roy:
Robot learning [TC Spotlight]. IEEE Robotics Autom. Mag. 16(3): 19-20 (2009) - 2008
- [j14]Takamitsu Matsubara, Jun Morimoto, Jun Nakanishi, Sang-Ho Hyon, Joshua G. Hale, Gordon Cheng:
Learning to Acquire Whole-Body Humanoid Center of Mass Movements to Achieve Dynamic Tasks. Adv. Robotics 22(10): 1125-1142 (2008) - [j13]Gen Endo, Jun Morimoto, Takamitsu Matsubara, Jun Nakanishi, Gordon Cheng:
Learning CPG-based Biped Locomotion with a Policy Gradient Method: Application to a Humanoid Robot. Int. J. Robotics Res. 27(2): 213-228 (2008) - [j12]Jun Morimoto, Gen Endo, Jun Nakanishi, Gordon Cheng:
A Biologically Inspired Biped Locomotion Strategy for Humanoid Robots: Modulation of Sinusoidal Patterns by a Coupled Oscillator Model. IEEE Trans. Robotics 24(1): 185-191 (2008) - [c26]Gordon Cheng, Sang-Ho Hyon, Ales Ude, Jun Morimoto, Joshua G. Hale, Joseph Hart, Jun Nakanishi, Darrin C. Bentivegna, Jessica K. Hodgins, Christopher G. Atkeson, Michael N. Mistry, Stefan Schaal, Mitsuo Kawato:
CB: Exploring neuroscience with a humanoid research platform. ICRA 2008: 1772-1773 - [c25]Sang-Ho Hyon, Jun Morimoto, Gordon Cheng:
Hierarchical motor learning and synthesis with passivity-based controller and phase oscillator. ICRA 2008: 2705-2710 - [c24]Jun Morimoto, Sang-Ho Hyon, Christopher G. Atkeson, Gordon Cheng:
Low-dimensional feature extraction for humanoid locomotion using kernel dimension reduction. ICRA 2008: 2711-2716 - [c23]Yuka Ariki, Jun Morimoto, Sang-Ho Hyon:
Behavior recognition with ground reaction force estimation and its application to imitation learning. IROS 2008: 2029-2034 - 2007
- [j11]Gordon Cheng, Sang-Ho Hyon, Jun Morimoto, Ales Ude, Joshua G. Hale, Glenn Colvin, Wayco Scroggin, Stephen C. Jacobsen:
CB: a humanoid research platform for exploring neuroscience. Adv. Robotics 21(10): 1097-1114 (2007) - [j10]Jun Morimoto, Kenji Doya:
Reinforcement Learning State Estimator. Neural Comput. 19(3): 730-756 (2007) - [j9]Jun Morimoto, Christopher G. Atkeson:
Learning Biped Locomotion. IEEE Robotics Autom. Mag. 14(2): 41-51 (2007) - [j8]Takamitsu Matsubara, Jun Morimoto, Jun Nakanishi, Masa-aki Sato, Kenji Doya:
Learning a dynamic policy by using policy gradient: application to biped walking. Syst. Comput. Jpn. 38(4): 25-38 (2007) - [c22]Jun Morimoto, Gen Endo, Sang-Ho Hyon, Gordon Cheng:
A simple approach to diverse humanoid locomotion. Humanoids 2007: 596-602 - [c21]Takamitsu Matsubara, Jun Morimoto, Jun Nakanishi, Sang-Ho Hyon, Joshua G. Hale, Gordon Cheng:
Learning to acquire whole-body humanoid CoM movements to achieve dynamic tasks. ICRA 2007: 2688-2693 - [c20]Jun Morimoto, Christopher G. Atkeson, Gen Endo, Gordon Cheng:
Improving humanoid locomotive performance with learnt approximated dynamics via Gaussian processes for regression. IROS 2007: 4234-4240 - 2006
- [j7]Takamitsu Matsubara, Jun Morimoto, Jun Nakanishi, Masa-aki Sato, Kenji Doya:
Learning CPG-based biped locomotion with a policy gradient method. Robotics Auton. Syst. 54(11): 911-920 (2006) - [c19]Gordon Cheng, Sang-Ho Hyon, Jun Morimoto, Ales Ude, Glenn Colvin, Wayco Scroggin, Stephen C. Jacobsen:
CB: A Humanoid Research Platform for Exploring NeuroScience. Humanoids 2006: 182-187 - [c18]Jun Morimoto, Gen Endo, Jun Nakanishi, Sang-Ho Hyon, Gordon Cheng, Darrin C. Bentivegna, Christopher G. Atkeson:
Modulation of Simple Sinusoidal Patterns by a Coupled Oscillator Model for Biped Walking. ICRA 2006: 1579-1584 - 2005
- [j6]Jun Morimoto, Kenji Doya:
Robust Reinforcement Learning. Neural Comput. 17(2): 335-359 (2005) - [c17]Gen Endo, Jun Morimoto, Takamitsu Matsubara, Jun Nakanishi, Gordon Cheng:
Learning CPG Sensory Feedback with Policy Gradient for Biped Locomotion for a Full-Body Humanoid. AAAI 2005: 1267-1273 - [c16]Takamitsu Matsubara, Jun Morimoto, Jun Nakanishi, Masa-aki Sato, Kenji Doya:
Learning CPG-based biped locomotion with a policy gradient method. Humanoids 2005: 208-213 - [c15]Gen Endo, Jun Nakanishi, Jun Morimoto, Gordon Cheng:
Experimental Studies of a Neural Oscillator for Biped Locomotion with QRIO. ICRA 2005: 596-602 - [c14]Jun Morimoto, Jun Nakanishi, Gen Endo, Gordon Cheng, Christopher G. Atkeson, Garth Zeglin:
Poincaré-Map-Based Reinforcement Learning For Biped Walking. ICRA 2005: 2381-2386 - [c13]Takamitsu Matsubara, Jun Morimoto, Jun Nakanishi, Masa-aki Sato, Kenji Doya:
Learning Sensory Feedback to CPG with Policy Gradient for Biped Locomotion. ICRA 2005: 4164-4169 - 2004
- [j5]Hiroyuki Miyamoto, Jun Morimoto, Kenji Doya, Mitsuo Kawato:
Reinforcement learning with via-point representation. Neural Networks 17(3): 299-305 (2004) - [j4]Jun Nakanishi, Jun Morimoto, Gen Endo, Gordon Cheng, Stefan Schaal, Mitsuo Kawato:
Learning from demonstration and adaptation of biped locomotion. Robotics Auton. Syst. 47(2-3): 79-91 (2004) - [c12]Jun Morimoto, Jun Nakanishi, Gen Endo, Gordon Cheng:
Acquisition of a biped walking pattern using a Poincare map. Humanoids 2004: 912-924 - [c11]Jun Nakanishi, Jun Morimoto, Gen Endo, Gordon Cheng, Stefan Schaal, Mitsuo Kawato:
A framework for learning biped locomotion with dynamical movement primitives. Humanoids 2004: 925-940 - [c10]Jun Morimoto, Gordon Cheng, Christopher G. Atkeson, Garth Zeglin:
A Simple Reinforcement Learning Algorithm for Biped Walking. ICRA 2004: 3030-3035 - [c9]Gen Endo, Jun Morimoto, Jun Nakanishi, Gordon Cheng:
An Empirical Exploration of a Neural Oscillator for Biped Locomotion Control. ICRA 2004: 3036-3042 - [c8]Jun Nakanishi, Jun Morimoto, Gen Endo, Gordon Cheng, Stefan Schaal, Mitsuo Kawato:
An empirical exploration of phase resetting for robust biped locomotion with dynamical movement primitives. IROS 2004: 919-924 - 2003
- [c7]Jun Morimoto, Garth Zeglin, Christopher G. Atkeson:
Minimax differential dynamic programming: application to a biped walking robot. IROS 2003: 1927-1932 - 2002
- [j3]Masanori Usui, Takahide Sugiyama, Masayasu Ishiko, Jun Morimoto, Hirokazu Saitoh, Masaki Ajioka:
Characterization of Trench MOS Gate Structures Utilizing Photon Emission Microscopy. Microelectron. Reliab. 42(9-11): 1647-1652 (2002) - [c6]Jun Morimoto, Christopher G. Atkeson:
Minimax Differential Dynamic Programming: An Application to Robust Biped Walking. NIPS 2002: 1539-1546 - [c5]Christopher G. Atkeson, Jun Morimoto:
Nonparametric Representation of Policies and Value Functions: A Trajectory-Based Approach. NIPS 2002: 1611-1618 - 2001
- [j2]Jun Morimoto, Kenji Doya:
Acquisition of stand-up behavior by a real robot using hierarchical reinforcement learning. Robotics Auton. Syst. 36(1): 37-51 (2001) - 2000
- [c4]Jun Morimoto, Kenji Doya:
Acquisition of Stand-up Behavior by a Real Robot using Hierarchical Reinforcement Learning. ICML 2000: 623-630 - [c3]Jun Morimoto, Kenji Doya:
Robust Reinforcement Learning. NIPS 2000: 1061-1067
1990 – 1999
- 1998
- [j1]Jun Morimoto, Kenji Doya:
Hierarchical reinforcement learning for motion learning: learning 'stand-up' trajectories. Adv. Robotics 13(3): 267-268 (1998) - [c2]Jun Morimoto, Kenji Doya:
Hierarchical Reinforcement Learning of Low-Dimensional Subgoals and High-Dimensional Trajectories. ICONIP 1998: 850-853 - [c1]Jun Morimoto, Kenji Doya:
Reinforcement learning of dynamic motor sequence: learning to stand up. IROS 1998: 1721-1726
Coauthor Index
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