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2020 – today
- 2024
[j58]Takanori Jin, Taisuke Kobayashi
, Takamitsu Matsubara:
Constrained footstep planning using model-based reinforcement learning in virtual constraint-based walking. Adv. Robotics 38(8): 525-545 (2024)- [j57]Naoto Komeno, Takamitsu Matsubara:
Incipient Slip Detection by Vibration Injection Into Soft Sensor. IEEE Robotics Autom. Lett. 9(4): 3251-3258 (2024) - [j56]Hanbit Oh, Takamitsu Matsubara:
Leveraging Demonstrator-Perceived Precision for Safe Interactive Imitation Learning of Clearance-Limited Tasks. IEEE Robotics Autom. Lett. 9(4): 3387-3394 (2024) - [j55]Yuki Kadokawa, Tomohito Kodera, Yoshihisa Tsurumine, Shinya Nishimura, Takamitsu Matsubara:
Robust iterative value conversion: Deep reinforcement learning for neurochip-driven edge robots. Robotics Auton. Syst. 181: 104782 (2024) - [c76]Tomoya Kitamura, Takumi Hachimine, Takamitsu Matsubara, Yuki Saito, Hiroshi Asai, Kouhei Ohnishi:
Analysis of Grinding Motion using Force/Tactile Sensation. ISIE 2024: 1-6 - [i38]Naoto Komeno, Takamitsu Matsubara:
Incipient Slip Detection by Vibration Injection into Soft Sensor. CoRR abs/2402.11879 (2024) - [i37]Hanbit Oh, Takamitsu Matsubara:
Leveraging Demonstrator-perceived Precision for Safe Interactive Imitation Learning of Clearance-limited Tasks. CoRR abs/2402.13466 (2024) - [i36]Yusei Naito, Tomohiko Jimbo, Tadashi Odashima, Takamitsu Matsubara:
Task-priority Intermediated Hierarchical Distributed Policies: Reinforcement Learning of Adaptive Multi-robot Cooperative Transport. CoRR abs/2404.02362 (2024) - [i35]Yuma Shida, Tomohiko Jimbo, Tadashi Odashima, Takamitsu Matsubara:
Reinforcement Learning of Multi-robot Task Allocation for Multi-object Transportation with Infeasible Tasks. CoRR abs/2404.11817 (2024) - [i34]Satoshi Yagi, Mitsunori Tada, Eiji Uchibe, Suguru Kanoga, Takamitsu Matsubara, Jun Morimoto:
Unsupervised Neural Motion Retargeting for Humanoid Teleoperation. CoRR abs/2406.00727 (2024) - [i33]Yuki Kadokawa, Tomohito Kodera, Yoshihisa Tsurumine, Shinya Nishimura, Takamitsu Matsubara:
Robust Iterative Value Conversion: Deep Reinforcement Learning for Neurochip-driven Edge Robots. CoRR abs/2408.13018 (2024) - 2023
- [j54]Tatsuya Sakuma, Takuya Kiyokawa, Takamitsu Matsubara, Jun Takamatsu, Takahiro Wada, Tsukasa Ogasawara:
Jamming Gripper-Inspired Soft Jig for Perceptive Parts Fixing. IEEE Access 11: 62187-62199 (2023) - [j53]Yuhwan Kwon, Hikaru Sasaki, Terushi Hirabayashi, Kaoru Kawabata, Takamitsu Matsubara:
Policy Optimization for Waste Crane Automation From Human Preferences. IEEE Access 11: 126524-126541 (2023) - [j52]Yaqiang Mo, Hikaru Sasaki, Takamitsu Matsubara, Kimitoshi Yamazaki:
Multi-step motion learning by combining learning-from-demonstration and policy-search. Adv. Robotics 37(9): 560-575 (2023) - [j51]Wendyam Eric Lionel Ilboudo, Taisuke Kobayashi, Takamitsu Matsubara:
AdaTerm: Adaptive T-distribution estimated robust moments for Noise-Robust stochastic gradient optimization. Neurocomputing 557: 126692 (2023) - [j50]Lingwei Zhu, Takamitsu Matsubara:
Cautious policy programming: exploiting KL regularization for monotonic policy improvement in reinforcement learning. Mach. Learn. 112(11): 4527-4562 (2023) - [j49]Hanbit Oh, Hikaru Sasaki, Brendan Michael, Takamitsu Matsubara:
Bayesian Disturbance Injection: Robust imitation learning of flexible policies for robot manipulation. Neural Networks 158: 42-58 (2023) - [j48]Hirotaka Tahara, Hikaru Sasaki, Hanbit Oh, Edgar Anarossi, Takamitsu Matsubara:
Disturbance Injection Under Partial Automation: Robust Imitation Learning for Long-Horizon Tasks. IEEE Robotics Autom. Lett. 8(5): 2724-2731 (2023) - [j47]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) - [j46]Cheng-Yu Kuo, Hirofumi Shin, Takamitsu Matsubara:
Reinforcement Learning With Energy-Exchange Dynamics for Spring-Loaded Biped Robot Walking. IEEE Robotics Autom. Lett. 8(10): 6243-6250 (2023) - [j45]Wataru Hatanaka, Ryota Yamashina, Takamitsu Matsubara:
Reinforcement Learning of Action and Query Policies With LTL Instructions Under Uncertain Event Detector. IEEE Robotics Autom. Lett. 8(11): 7010-7017 (2023) - [j44]Kazuki Shibata, Tomohiko Jimbo, Takamitsu Matsubara:
Deep reinforcement learning of event-triggered communication and consensus-based control for distributed cooperative transport. Robotics Auton. Syst. 159: 104307 (2023) - [j43]Yuki Kadokawa, Lingwei Zhu, Yoshihisa Tsurumine, Takamitsu Matsubara:
Cyclic policy distillation: Sample-efficient sim-to-real reinforcement learning with domain randomization. Robotics Auton. Syst. 165: 104425 (2023) - [c75]Edgar Anarossi, Hirotaka Tahara, Naoto Komeno, Takamitsu Matsubara:
Deep Segmented DMP Networks for Learning Discontinuous Motions. CASE 2023: 1-7 - [c74]Wendyam Eric Lionel Ilboudo, Taisuke Kobayashi, Takamitsu Matsubara:
Domains as Objectives: Multi-Domain Reinforcement Learning with Convex-Coverage Set Learning for Domain Uncertainty Awareness. IROS 2023: 5622-5629 - [i32]Lingwei Zhu, Zheng Chen, Takamitsu Matsubara, Martha White:
Generalized Munchausen Reinforcement Learning using Tsallis KL Divergence. CoRR abs/2301.11476 (2023) - [i31]Hirotaka Tahara, Hikaru Sasaki, Hanbit Oh, Edgar Anarossi, Takamitsu Matsubara:
Disturbance Injection under Partial Automation: Robust Imitation Learning for Long-horizon Tasks. CoRR abs/2303.12375 (2023) - [i30]Takumi Hachimine, Jun Morimoto, Takamitsu Matsubara:
Learning to Shape by Grinding: Cutting-surface-aware Model-based Reinforcement Learning. CoRR abs/2308.02150 (2023) - [i29]Edgar Anarossi, Hirotaka Tahara, Naoto Komeno, Takamitsu Matsubara:
Deep Segmented DMP Networks for Learning Discontinuous Motions. CoRR abs/2309.00320 (2023) - [i28]Wataru Hatanaka, Ryota Yamashina, Takamitsu Matsubara:
Reinforcement Learning of Action and Query Policies with LTL Instructions under Uncertain Event Detector. CoRR abs/2309.02722 (2023) - 2022
- [j42]Brendan Michael, Akifumi Ise, Kaoru Kawabata, Takamitsu Matsubara:
Task-Relevant Encoding of Domain Knowledge in Dynamics Modeling: Application to Furnace Forecasting From Video. IEEE Access 10: 4615-4627 (2022) - [j41]Yujun Lai, Gavin Paul, Yunduan Cui, Takamitsu Matsubara:
User intent estimation during robot learning using physical human robot interaction primitives. Auton. Robots 46(2): 421-436 (2022) - [j40]Lingwei Zhu, Go Takami, Mizuo Kawahara, Hiroaki Kanokogi, Takamitsu Matsubara:
Alleviating parameter-tuning burden in reinforcement learning for large-scale process control. Comput. Chem. Eng. 158: 107658 (2022) - [j39]Taisuke Kobayashi, Yutaro Ikawa, Takamitsu Matsubara:
Sample-efficient gear-ratio optimization for biomechanical energy harvester. Int. J. Intell. Robotics Appl. 6(1): 10-22 (2022) - [j38]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) - [j37]Yuhwan Kwon, Yoshihisa Tsurumine, Takeshi Shimmura, Sadao Kawamura, Takamitsu Matsubara:
Physically Consistent Preferential Bayesian Optimization for Food Arrangement. IEEE Robotics Autom. Lett. 7(4): 11863-11870 (2022) - [j36]Felix von Drigalski, Kazumi Kasaura, Cristian C. Beltran-Hernandez, Masashi Hamaya, Kazutoshi Tanaka, Takamitsu Matsubara:
Uncertainty-Aware Manipulation Planning Using Gravity and Environment Geometry. IEEE Robotics Autom. Lett. 7(4): 11942-11949 (2022) - [j35]Yoshihisa Tsurumine, Takamitsu Matsubara:
Goal-aware generative adversarial imitation learning from imperfect demonstration for robotic cloth manipulation. Robotics Auton. Syst. 158: 104264 (2022) - [c73]Cheng-Yu Kuo, Hirofumi Shin, Takumi Kamioka, Takamitsu Matsubara:
TDE2-MBRL: Energy-exchange Dynamics Learning with Task Decomposition for Spring-loaded Bipedal Robot Locomotion. Humanoids 2022: 550-557 - [c72]Hirotaka Tahara, Hikaru Sasaki, Hanbit Oh, Brendan Michael, Takamitsu Matsubara:
Disturbance-injected Robust Imitation Learning with Task Achievement. ICRA 2022: 2466-2472 - [c71]Hikaru Sasaki, Terushi Hirabayashi, Kaoru Kawabata, Takamitsu Matsubara:
Gaussian Process Self-triggered Policy Search in Weakly Observable Environments. ICRA 2022: 5946-5952 - [c70]Naoto Komeno, Brendan Michael, Katharina Küchler, Edgar Anarossi, Takamitsu Matsubara:
Deep Koopman with Control: Spectral Analysis of Soft Robot Dynamics. SICE 2022: 333-340 - [c69]Atsuki Nagata, Takamitsu Matsubara, Kenji Sugimoto:
Disturbance Suppression in Feedback Error Learning Control. SICE 2022: 944-949 - [c68]Yoshihisa Tsurumine, Takamitsu Matsubara:
Variationally Autoencoded Dynamic Policy Programming for Robotic Cloth Manipulation Planning based on Raw Images. SII 2022: 416-421 - [i27]Hikaru Sasaki, Terushi Hirabayashi, Kaoru Kawabata, Takamitsu Matsubara:
Gaussian Process Self-triggered Policy Search in Weakly Observable Environments. CoRR abs/2205.03552 (2022) - [i26]Hirotaka Tahara, Hikaru Sasaki, Hanbit Oh, Brendan Michael, Takamitsu Matsubara:
Disturbance-Injected Robust Imitation Learning with Task Achievement. CoRR abs/2205.04195 (2022) - [i25]Lingwei Zhu, Zheng Chen, Eiji Uchibe, Takamitsu Matsubara:
q-Munchausen Reinforcement Learning. CoRR abs/2205.07467 (2022) - [i24]Lingwei Zhu, Zheng Chen, Eiji Uchibe, Takamitsu Matsubara:
Enforcing KL Regularization in General Tsallis Entropy Reinforcement Learning via Advantage Learning. CoRR abs/2205.07885 (2022) - [i23]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) - [i22]Yuki Kadokawa, Lingwei Zhu, Yoshihisa Tsurumine, Takamitsu Matsubara:
Cyclic Policy Distillation: Sample-Efficient Sim-to-Real Reinforcement Learning with Domain Randomization. CoRR abs/2207.14561 (2022) - [i21]Yoshihisa Tsurumine, Takamitsu Matsubara:
Goal-Aware Generative Adversarial Imitation Learning from Imperfect Demonstration for Robotic Cloth Manipulation. CoRR abs/2209.10149 (2022) - [i20]Yuhwan Kwon, Yoshihisa Tsurumine, Takeshi Shimmura, Sadao Kawamura, Takamitsu Matsubara:
Physically Consistent Preferential Bayesian Optimization for Food Arrangement. CoRR abs/2209.10602 (2022) - [i19]Naoto Komeno, Brendan Michael, Katharina Küchler, Edgar Anarossi, Takamitsu Matsubara:
Deep Koopman with Control: Spectral Analysis of Soft Robot Dynamics. CoRR abs/2210.07563 (2022) - [i18]Hanbit Oh, Hikaru Sasaki, Brendan Michael, Takamitsu Matsubara:
Bayesian Disturbance Injection: Robust Imitation Learning of Flexible Policies for Robot Manipulation. CoRR abs/2211.03393 (2022) - [i17]Kazuki Shibata, Tomohiko Jimbo, Takamitsu Matsubara:
Deep reinforcement learning of event-triggered communication and consensus-based control for distributed cooperative transport. CoRR abs/2212.01958 (2022) - [i16]Kazuki Shibata, Tomohiko Jimbo, Tadashi Odashima, Keisuke Takeshita, Takamitsu Matsubara:
Learning Locally, Communicating Globally: Reinforcement Learning of Multi-robot Task Allocation for Cooperative Transport. CoRR abs/2212.02692 (2022) - 2021
- [j34]Keiji Nagatani, Masato Abe, Koichi Osuka, Pang-jo Chun, Takayuki Okatani, Mayuko Nishio, Shota Chikushi, Takamitsu Matsubara, Yusuke Ikemoto, Hajime Asama:
Innovative technologies for infrastructure construction and maintenance through collaborative robots based on an open design approach. Adv. Robotics 35(11): 715-722 (2021) - [j33]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) - [j32]Yunduan Cui, Shigeki Osaki, Takamitsu Matsubara:
Autonomous boat driving system using sample-efficient model predictive control-based reinforcement learning approach. J. Field Robotics 38(3): 331-354 (2021) - [j31]Hikaru Sasaki, Takamitsu Matsubara:
Variational policy search using sparse Gaussian process priors for learning multimodal optimal actions. Neural Networks 143: 291-302 (2021) - [j30]Cheng-Yu Kuo, Andreas Schaarschmidt, Yunduan Cui, Tamim Asfour, Takamitsu Matsubara:
Uncertainty-Aware Contact-Safe Model-Based Reinforcement Learning. IEEE Robotics Autom. Lett. 6(2): 3918-3925 (2021) - [j29]Naoto Komeno, Takamitsu Matsubara:
Tactile Perception Based on Injected Vibration in Soft Sensor. IEEE Robotics Autom. Lett. 6(3): 5365-5372 (2021) - [j28]Yuki Kadokawa, Yoshihisa Tsurumine, Takamitsu Matsubara:
Binarized P-Network: Deep Reinforcement Learning of Robot Control from Raw Images on FPGA. IEEE Robotics Autom. Lett. 6(4): 8545-8552 (2021) - [c67]Lingwei Zhu, Toshinori Kitamura, Takamitsu Matsubara:
Cautious Actor-Critic. ACML 2021: 220-235 - [c66]Toshinori Kitamura, Lingwei Zhu, Takamitsu Matsubara:
Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning. ACML 2021: 918-931 - [c65]Hanbit Oh, Hikaru Sasaki, Brendan Michael, Takamitsu Matsubara:
Bayesian Disturbance Injection: Robust Imitation Learning of Flexible Policies. ICRA 2021: 8629-8635 - [c64]Kazuki Shibata, Tomohiko Jimbo, Takamitsu Matsubara:
Deep reinforcement learning of event-triggered communication and control for multi-agent cooperative transport. ICRA 2021: 8671-8677 - [c63]Kazutoshi Tanaka, Masashi Hamaya, Devwrat Joshi, Felix von Drigalski, Ryo Yonetani, Takamitsu Matsubara, Yoshihisa Ijiri:
Learning Robotic Contact Juggling. IROS 2021: 958-964 - [i15]Hanbit Oh, Hikaru Sasaki, Brendan Michael, Takamitsu Matsubara:
Bayesian Disturbance Injection: Robust Imitation Learning of Flexible Policies. CoRR abs/2103.13623 (2021) - [i14]Kazuki Shibata, Tomohiko Jimbo, Takamitsu Matsubara:
Deep reinforcement learning of event-triggered communication and control for multi-agent cooperative transport. CoRR abs/2103.15260 (2021) - [i13]Taisuke Kobayashi, Yutaro Ikawa, Takamitsu Matsubara:
Sample-efficient Gear-ratio Optimization for Biomechanical Energy Harvester. CoRR abs/2104.00382 (2021) - [i12]Naoto Komeno, Takamitsu Matsubara:
Tactile Perception based on Injected Vibration in Soft Sensor. CoRR abs/2104.09790 (2021) - [i11]Kazuki Shibata, Tatsuya Miyano, Tomohiko Jimbo, Takamitsu Matsubara:
Robust shape estimation with false-positive contact detection. CoRR abs/2104.10318 (2021) - [i10]Hikaru Sasaki, Takamitsu Matsubara:
Variational Policy Search using Sparse Gaussian Process Priors for Learning Multimodal Optimal Actions. CoRR abs/2106.07125 (2021) - [i9]Lingwei Zhu, Toshinori Kitamura, Takamitsu Matsubara:
Cautious Actor-Critic. CoRR abs/2107.05217 (2021) - [i8]Lingwei Zhu, Toshinori Kitamura, Takamitsu Matsubara:
Cautious Policy Programming: Exploiting KL Regularization in Monotonic Policy Improvement for Reinforcement Learning. CoRR abs/2107.05798 (2021) - [i7]Toshinori Kitamura, Lingwei Zhu, Takamitsu Matsubara:
Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning. CoRR abs/2107.07659 (2021) - [i6]Yuki Kadokawa, Yoshihisa Tsurumine, Takamitsu Matsubara:
Binarized P-Network: Deep Reinforcement Learning of Robot Control from Raw Images on FPGA. CoRR abs/2109.04966 (2021) - 2020
- [j27]Yunduan Cui, Junichiro Ooga, Akihito Ogawa, Takamitsu Matsubara:
Probabilistic active filtering with gaussian processes for occluded object search in clutter. Appl. Intell. 50(12): 4310-4324 (2020) - [j26]Hikaru Sasaki, Terushi Hirabayashi, Kaoru Kawabata, Yukio Onuki, Takamitsu Matsubara:
Bayesian Policy Optimization for Waste Crane With Garbage Inhomogeneity. IEEE Robotics Autom. Lett. 5(3): 4533-4540 (2020) - [j25]Cristian Camilo Beltran-Hernandez, Damien Petit, Ixchel Georgina Ramirez-Alpizar, Takayuki Nishi, Shinichi Kikuchi, Takamitsu Matsubara, Kensuke Harada:
Learning Force Control for Contact-Rich Manipulation Tasks With Rigid Position-Controlled Robots. IEEE Robotics Autom. Lett. 5(4): 5709-5716 (2020) - [j24]Tomoya Miyamoto, Hikaru Sasaki, Takamitsu Matsubara:
Exploiting Visual-Outer Shape for Tactile-Inner Shape Estimation of Objects Covered with Soft Materials. IEEE Robotics Autom. Lett. 5(4): 6278-6285 (2020) - [j23]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) - [j22]Kazuki Shibata, Tatsuya Miyano, Tomohiko Jimbo, Takamitsu Matsubara:
Robust shape estimation with false-positive contact detection. Robotics Auton. Syst. 129: 103527 (2020) - [c62]Cheng-Yu Kuo, Yunduan Cui, Takamitsu Matsubara:
Sample-and-computation-efficient Probabilistic Model Predictive Control with Random Features. ICRA 2020: 307-313 - [c61]Felix Von Drigalski, Shohei Taniguchi, Robert Lee, Takamitsu Matsubara, Masashi Hamaya, Kazutoshi Tanaka, Yoshihisa Ijiri:
Contact-based in-hand pose estimation using Bayesian state estimation and particle filtering. ICRA 2020: 7294-7299 - [c60]Lingwei Zhu, Yunduan Cui, Takamitsu Matsubara:
Dynamic Actor-Advisor Programming for Scalable Safe Reinforcement Learning. ICRA 2020: 10681-10687 - [c59]Masashi Hamaya, Felix von Drigalski, Takamitsu Matsubara, Kazutoshi Tanaka, Robert Lee, Chisato Nakashima, Yoshiya Shibata, Yoshihisa Ijiri:
Learning Soft Robotic Assembly Strategies from Successful and Failed Demonstrations. IROS 2020: 8309-8315 - [c58]Yuhwan Kwon, Takumi Kaneko, Yoshihisa Tsurumine, Hikaru Sasaki, Kimiko Motonaka, Seiji Miyoshi, Takamitsu Matsubara:
Combining Model Predictive Path Integral with Kalman Variational Auto-encoder for Robot Control from Raw Images. SII 2020: 271-276 - [c57]Junki Matsuoka, Yoshihisa Tsurumine, Yuhwan Kwon, Takamitsu Matsubara, Takeshi Shimmura, Sadao Kawamura:
Learning Food-arrangement Policies from Raw Images with Generative Adversarial Imitation Learning. UR 2020: 93-98 - [i5]Cristian Camilo Beltran-Hernandez, Damien Petit, Ixchel Georgina Ramirez-Alpizar, Takayuki Nishi, Shinichi Kikuchi, Takamitsu Matsubara, Kensuke Harada:
Learning Contact-Rich Manipulation Tasks with Rigid Position-Controlled Robots: Learning to Force Control. CoRR abs/2003.00628 (2020) - [i4]Lingwei Zhu, Takamitsu Matsubara:
Ensuring Monotonic Policy Improvement in Entropy-regularized Value-based Reinforcement Learning. CoRR abs/2008.10806 (2020) - [i3]Cheng-Yu Kuo, Andreas Schaarschmidt, Yunduan Cui, Tamim Asfour, Takamitsu Matsubara:
Uncertainty-aware Contact-safe Model-based Reinforcement Learning. CoRR abs/2010.08169 (2020)
2010 – 2019
- 2019
- [j21]Akihiko Yamaguchi, Takamitsu Matsubara, Nikolaus Vahrenkamp, Oliver Kroemer, Kensuke Harada:
Special issue on artificial intelligence and machine learning for robotic manipulation. Adv. Robotics 33(22): 1155 (2019) - [j20]Yunduan Cui, James Poon, Jaime Valls Miró, Kimitoshi Yamazaki, Kenji Sugimoto, Takamitsu Matsubara:
Environment-adaptive interaction primitives through visual context for human-robot motor skill learning. Auton. Robots 43(5): 1225-1240 (2019) - [j19]James Poon, Yunduan Cui, Jaime Valls Miró, Takamitsu Matsubara:
Learning from demonstration for locally assistive mobility aids. Int. J. Intell. Robotics Appl. 3(3): 255-268 (2019) - [j18]Yoshihisa Tsurumine, Yunduan Cui, Eiji Uchibe, Takamitsu Matsubara:
Deep reinforcement learning with smooth policy update: Application to robotic cloth manipulation. Robotics Auton. Syst. 112: 72-83 (2019) - [c56]Takumi Kaneko, Yoshihisa Tsurumine, James Poon, Yukio Onuki, Yingda Dai, Kaoru Kawabata, Takamitsu Matsubara:
Learning Deep Dynamical Models of a Waste Incineration Plant from In-furnace Images and Process Data. CASE 2019: 873-878 - [c55]Yoshihisa Tsurumine, Yunduan Cui, Kimitoshi Yamazaki, Takamitsu Matsubara:
Generative Adversarial Imitation Learning with Deep P-Network for Robotic Cloth Manipulation. Humanoids 2019: 274-280 - [c54]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 - [c53]Hikaru Sasaki, Takamitsu Matsubara:
Multimodal Policy Search using Overlapping Mixtures of Sparse Gaussian Process Prior. ICRA 2019: 2433-2439 - [c52]James Poon, Yunduan Cui, Junichiro Ooga, Akihito Ogawa, Takamitsu Matsubara:
Probabilistic Active Filtering for Object Search in Clutter. ICRA 2019: 7256-7261 - [c51]Yunduan Cui, Shigeki Osaki, Takamitsu Matsubara:
Reinforcement Learning Boat Autopilot: A Sample-efficient and Model Predictive Control based Approach. IROS 2019: 2868-2875 - [i2]Yunduan Cui, Shigeki Osaki, Takamitsu Matsubara:
Reinforcement Learning Ship Autopilot: Sample-efficient and Model Predictive Control-based Approach. CoRR abs/1901.07905 (2019) - 2018
- [c50]Yutaro Ikawa, Taisuke Kobayashi, Takamitsu Matsubara:
Biomechanical Energy Harvester with Continuously Variable Transmission: Prototyping and Preliminary Evaluation. AIM 2018: 1045-1050 - [c49]Daniel F. N. Gordon, Takamitsu Matsubara, Tomoyuki Noda, Tatsuya Teramae, Jun Morimoto, Sethu Vijayakumar:
Bayesian Optimisation of Exoskeleton Design Parameters. BioRob 2018: 653-658 - [c48]Takamitsu Matsubara, Yu Norinaga, Yuto Ozawa, Yunduan Cui:
Policy Transfer from Simulations to Real World by Transfer Component Analysis. CASE 2018: 264-269 - [c47]Yunduan Cui, Lingwei Zhu, Morihiro Fujisaki, Hiroaki Kanokogi, Takamitsu Matsubara:
Factorial Kernel Dynamic Policy Programming for Vinyl Acetate Monomer Plant Model Control. CASE 2018: 304-309 - [c46]Yujun Lai, James Poon, Gavin Paul, Haifeng Han, Takamitsu Matsubara:
Probabilistic Pose Estimation of Deformable Linear Objects. CASE 2018: 471-476 - [c45]James Poon, Yunduan Cui, Jaime Valls Miró, Takamitsu Matsubara:
Learning Mobility Aid Assistance via Decoupled Observation Models. ICARCV 2018: 1903-1910 - [c44]Yaqiang Mo, Takamitsu Matsubara, Kimitoshi Yamazaki:
Folding Behavior Acquisition of A Shirt Placed on the Chest of a Dual-Arm Robot. ICIA 2018: 190-195 - 2017
- [j17]Yunduan Cui, Takamitsu Matsubara, Kenji Sugimoto:
Pneumatic artificial muscle-driven robot control using local update reinforcement learning. Adv. Robotics 31(8): 397-412 (2017) - [j16]Ming Ding, Takamitsu Matsubara, Yoshihito Funaki, Ryojun Ikeura, Toshiharu Mukai, Tsukasa Ogasawara:
Generation of comfortable lifting motion for a human transfer assistant robot. Int. J. Intell. Robotics Appl. 1(1): 74-85 (2017) - [j15]Yunduan Cui, Takamitsu Matsubara, Kenji Sugimoto:
Kernel dynamic policy programming: Applicable reinforcement learning to robot systems with high dimensional states. Neural Networks 94: 13-23 (2017) - [j14]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) - [j13]Takamitsu Matsubara, Kotaro Shibata:
Active tactile exploration with uncertainty and travel cost for fast shape estimation of unknown objects. Robotics Auton. Syst. 91: 314-326 (2017) - [c43]Haifeng Han, Gavin Paul, Takamitsu Matsubara:
Model-based reinforcement learning approach for deformable linear object manipulation. CASE 2017: 750-755 - [c42]Yosuke Koishihara, Solvi Arnold, Kimitoshi Yamazaki, Takamitsu Matsubara:
Hanging work of T-shirt in consideration of deformability and stretchability. ICIA 2017: 130-135 - [c41]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 - [c40]James Poon, Yunduan Cui, Jaime Valls Miró, Takamitsu Matsubara, Kenji Sugimoto:
Local driving assistance from demonstration for mobility aids. ICRA 2017: 5935-5941 - [c39]Yoshihisa Tsurumine, Yunduan Cui, Eiji Uchibe, Takamitsu Matsubara:
Deep dynamic policy programming for robot control with raw images. IROS 2017: 1545-1550 - [c38]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 - [c37]Masaki Murase, Kimitoshi Yamazaki, Takamitsu Matsubara:
Kullback Leibler control approach to rubber band manipulation. SII 2017: 680-685 - [c36]Yuki Ishikura, Takamitsu Matsubara, Kenji Sugimoto, Yusuke Kato, Tsuyoshi Inoue, Jun Ozawa:
Learning discriminative intention predictors for sit-to-stand assistance. SII 2017: 962-967 - 2016
- [j12]Daisuke Tanaka, Takamitsu Matsubara, Kenji Sugimoto:
Input-Output Manifold Learning with State Space Models. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 99-A(6): 1179-1187 (2016) - [c35]Takamitsu Matsubara, Kotaro Shibata, Kenji Sugimoto:
Active touch point selection with travel cost in tactile exploration for fast shape estimation of unknown objects. AIM 2016: 1115-1120 - [c34]Takamitsu Matsubara, Yoshihito Funaki, Ming Ding, Tsukasa Ogasawara, Kenji Sugimoto:
Data-efficient human training of a care motion controller for human transfer assistant robots using Bayesian optimization. BioRob 2016: 606-611 - [c33]Yunduan Cui, Takamitsu Matsubara, Kenji Sugimoto:
Kernel dynamic policy programming: Practical reinforcement learning for high-dimensional robots. Humanoids 2016: 662-667 - [c32]Yunduan Cui, James Poon, Takamitsu Matsubara, Jaime Valls Miró, Kenji Sugimoto, Kimitoshi Yamazaki:
Environment-adaptive interaction primitives for human-robot motor skill learning. Humanoids 2016: 711-717 - [c31]Yuka Ariki, Takamitsu Matsubara, Sang-Ho Hyon:
Latent Kullback-Leibler control for dynamic imitation learning of whole-body behaviors in humanoid robots. Humanoids 2016: 946-951 - [c30]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 - [c29]Nahum Álvarez, Kimitoshi Yamazaki, Takamitsu Matsubara:
An approach to realistic physical simulation of digitally captured deformable linear objects. SIMPAR 2016: 135-140 - 2015
- [j11]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) - [j10]Takamitsu Matsubara, Takaya Asakura, Kenji Sugimoto:
Dynamic Linear Bellman Combination of Optimal Policies for Solving New Tasks. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 98-A(10): 2187-2190 (2015) - [c28]Yunduan Cui, Takamitsu Matsubara, Kenji Sugimoto:
Local Update Dynamic Policy Programming in reinforcement learning of pneumatic artificial muscle-driven humanoid hand control. Humanoids 2015: 1083-1089 - [c27]Takamitsu Matsubara, Takahiro Hasegawa, Kenji Sugimoto:
Reinforcement learning of shared control for dexterous telemanipulation: Application to a page turning skill. RO-MAN 2015: 343-348 - [c26]Takamitsu Matsubara, Jaime Valls Miró, Daisuke Tanaka, James Poon, Kenji Sugimoto:
Sequential intention estimation of a mobility aid user for intelligent navigational assistance. RO-MAN 2015: 444-449 - 2014
- [c25]Takamitsu Matsubara, Hiroaki Takada, Kenji Sugimoto:
Task-adaptive inertial parameter estimation of rigid-body dynamics with modeling error for model-based control using covariate shift adaptation. AIM 2014: 476-482 - [c24]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 - [c23]Daisuke Tanaka, Takamitsu Matsubara, Kenji Sugimoto:
An optimal control approach for exploratory actions in active tactile object recognition. Humanoids 2014: 787-793 - [c22]Daisuke Tanaka, Takamitsu Matsubara, Kentaro Ichien, Kenji Sugimoto:
Object manifold learning with action features for active tactile object recognition. IROS 2014: 608-614 - [c21]Nishanth Koganti, Tomoya Tamei, Takamitsu Matsubara, Tomohiro Shibata:
Real-time estimation of Human-Cloth topological relationship using depth sensor for robotic clothing assistance. RO-MAN 2014: 124-129 - [c20]Takamitsu Matsubara, Vicenç Gómez, Hilbert J. Kappen:
Latent Kullback Leibler Control for Continuous-State Systems using Probabilistic Graphical Models. UAI 2014: 583-592 - [i1]Takamitsu Matsubara, Vicenç Gómez, Hilbert J. Kappen:
Latent Kullback Leibler Control for Continuous-State Systems using Probabilistic Graphical Models. CoRR abs/1406.0993 (2014) - 2013
- [j9]Takamitsu Matsubara, Daisuke Shinohara, Masatsugu Kidode:
Reinforcement learning of a motor skill for wearing a T-shirt using topology coordinates. Adv. Robotics 27(7): 513-524 (2013) - [j8]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) - [c19]Nishanth Koganti, Tomoya Tamei, Takamitsu Matsubara, Tomohiro Shibata:
Estimation of Human Cloth Topological Relationship using Depth Sensor for Robotic Clothing Assistance. AIR 2013: 36:1-36:6 - 2012
- [j7]Takamitsu Matsubara, Sang-Ho Hyon, Jun Morimoto:
Real-time stylistic prediction for whole-body human motions. Neural Networks 25: 191-199 (2012) - [c18]Takamitsu Matsubara, Akimasa Uchikata, Jun Morimoto:
Spatio-temporal synchronization of periodic movements by style-phase adaptation: Application to biped walking. ICRA 2012: 524-530 - [c17]Takamitsu Matsubara, Akimasa Uchikata, Jun Morimoto:
Full-body exoskeleton robot control for walking assistance by style-phase adaptive pattern generation. IROS 2012: 3914-3920 - [c16]Takamitsu Matsubara, Shizuko Matsuzoe, Masatsugu Kidode:
Adaptive choreography for user's preferences on personal robots. RO-MAN 2012: 1032-1038 - 2011
- [j6]Takamitsu Matsubara, Sang-Ho Hyon, Jun Morimoto:
Learning parametric dynamic movement primitives from multiple demonstrations. Neural Networks 24(5): 493-500 (2011) - [c15]Takamitsu Matsubara, Tomoyuki Noda, Sang-Ho Hyon, Jun Morimoto:
An optimal control approach for hybrid actuator system. Humanoids 2011: 300-305 - [c14]Tomoya Tamei, Takamitsu Matsubara, Akshara Rai, Tomohiro Shibata:
Reinforcement learning of clothing assistance with a dual-arm robot. Humanoids 2011: 733-738 - [c13]Sang-Ho Hyon, Jun Morimoto, Takamitsu Matsubara, Tomoyuki Noda, Mitsuo Kawato:
XoR: Hybrid drive exoskeleton robot that can balance. IROS 2011: 3975-3981 - [c12]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 - [c11]Yasuhito Horiguchi, Takamitsu Matsubara, Masatsugu Kidode:
Learning Parametric Inverse Dynamics Models from multiple conditions for fast adaptive computed torque control. ROBIO 2011: 2670-2675 - [c10]Daisuke Shinohara, Takamitsu Matsubara, Masatsugu Kidode:
Learning motor skills with non-rigid materials by reinforcement learning. ROBIO 2011: 2676-2681 - 2010
- [c9]Takamitsu Matsubara, Sang-Ho Hyon, Jun Morimoto:
Learning Parametric Dynamic Movement Primitives from Multiple Demonstrations. ICONIP (1) 2010: 347-354 - [c8]Yasuhito Horiguchi, Takamitsu Matsubara, Masatsugu Kidode:
Learning Basis Representations of Inverse Dynamics Models for Real-Time Adaptive Control. ICONIP (2) 2010: 668-675 - [c7]Djordje Mitrovic, Sho Nagashima, Stefan Klanke, Takamitsu Matsubara, Sethu Vijayakumar:
Optimal Feedback Control for anthropomorphic manipulators. ICRA 2010: 4143-4150 - [c6]Takamitsu Matsubara, Sang-Ho Hyon, Jun Morimoto:
Learning Stylistic Dynamic Movement Primitives from multiple demonstrations. IROS 2010: 1277-1283 - [c5]Takamitsu Matsubara, Tetsuro Morimura, Jun Morimoto:
Adaptive Step-size Policy Gradients with Average Reward Metric. ACML 2010: 285-298
2000 – 2009
- 2008
- [j5]Joshua G. Hale, Benjamin Hohl, Sang-Ho Hyon, Takamitsu Matsubara, Eduardo Martin Moraud, Gordon Cheng:
Highly Precise Dynamic Simulation Environment for Humanoid Robots. Adv. Robotics 22(10): 1075-1105 (2008) - [j4]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) - [j3]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) - 2007
- [j2]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) - [c4]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 - 2006
- [j1]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) - 2005
- [c3]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 - [c2]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 - [c1]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
Coauthor Index
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