default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDJun Morimoto
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
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
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-13 23:46 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
