Takamitsu Matsubara

发表

Learning Sensory Feedback to CPG with Policy Gradient for Biped Locomotion

Jun Morimoto, Jun Nakanishi, Takamitsu Matsubara, 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

Learning CPG-based Biped Locomotion with a Policy Gradient Method: Application to a Humanoid Robot

Jun Morimoto, Gen Endo, Jun Nakanishi, 2005, 5th IEEE-RAS International Conference on Humanoid Robots, 2005..

Learning CPG Sensory Feedback with Policy Gradient for Biped Locomotion for a Full-Body Humanoid

Jun Morimoto, Gen Endo, Jun Nakanishi, 2005, AAAI.

Optimal Feedback Control for anthropomorphic manipulators

Takamitsu Matsubara, Sethu Vijayakumar, Djordje Mitrovic, 2010, 2010 IEEE International Conference on Robotics and Automation.

Bayesian Optimisation of Exoskeleton Design Parameters

Jun Morimoto, Takamitsu Matsubara, Sethu Vijayakumar, 2018, 2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob).

Learning parametric dynamic movement primitives from multiple demonstrations

Jun Morimoto, Takamitsu Matsubara, Sang-Ho Hyon, 2011, Neural Networks.

Adaptive choreography for user's preferences on personal robots

Takamitsu Matsubara, Masatsugu Kidode, Shizuko Matsuzoe, 2012, 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication.

Autonomous boat driving system using sample‐efficient model predictive control‐based reinforcement learning approach

Takamitsu Matsubara, Cui Yunduan, Shigeki Osaki, 2020, J. Field Robotics.

Full-body exoskeleton robot control for walking assistance by style-phase adaptive pattern generation

Jun Morimoto, Takamitsu Matsubara, Akimasa Uchikata, 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Active touch point selection with travel cost in tactile exploration for fast shape estimation of unknown objects

Takamitsu Matsubara, Kotaro Shibata, Kenji Sugimoto, 2016, 2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM).

Learning Soft Robotic Assembly Strategies from Successful and Failed Demonstrations

Felix von Drigalski, Takamitsu Matsubara, Masashi Hamaya, 2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Pneumatic artificial muscle-driven robot control using local update reinforcement learning

Takamitsu Matsubara, Kenji Sugimoto, Yunduan Cui, 2017, Adv. Robotics.

Design of physical user–robot interactions for model identification of soft actuators on exoskeleton robots

J. Morimoto, Takamitsu Matsubara, T. Noda, 2019, Int. J. Robotics Res..

On-line Stylistic Predictionfor Human Periodic Motions

J. Morimoto, Takamitsu Matsubara, S. Hyon, 2010, Neuroscience Research.

An approach to Short Plan Construction for Deformable Linear Object Manipulation

Kimitoshi Yamazaki, Takamitsu Matsubara, Takamitsu Matsubara, .

Object Manifold Learning Based on Tactile and Action Information and Its Application to Active Object Identification

Takamitsu Matsubara, ○Daisuke Tanaka, Kenji Sugimoto Naist, 2013 .

Gaussian Process Self-triggered Policy Search in Weakly Observable Environments

Takamitsu Matsubara, Hikaru Sasaki, T. Hirabayashi, 2022, 2022 International Conference on Robotics and Automation (ICRA).

Disturbance-injected Robust Imitation Learning with Task Achievement

Takamitsu Matsubara, Hikaru Sasaki, Hirotaka Tahara, 2022, IEEE International Conference on Robotics and Automation.

System Identification with Input-Output Manifold Learning

Takamitsu Matsubara, Kenji Sugimoto, Daisuke Tanaka, 2013 .

Cyclic Policy Distillation: Sample-Efficient Sim-to-Real Reinforcement Learning with Domain Randomization

Takamitsu Matsubara, Lingwei Zhu, Y. Kadokawa, 2022, ArXiv.

Learning Robotic Contact Juggling

Takamitsu Matsubara, Ryo Yonetani, Masashi Hamaya, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Disturbance Suppression in Feedback Error Learning Control

Takamitsu Matsubara, Kenji Sugimoto, Atsuki Nagata, 2022, 2022 61st Annual Conference of the Society of Instrument and Control Engineers (SICE).

Randomized-to-Canonical Model Predictive Control for Real-World Visual Robotic Manipulation

J. Morimoto, E. Uchibe, Takamitsu Matsubara, 2022, IEEE Robotics and Automation Letters.

Task-Relevant Encoding of Domain Knowledge in Dynamics Modeling: Application to Furnace Forecasting From Video

Takamitsu Matsubara, Kaoru Kawabata, B. Michael, 2022, IEEE Access.

Physically Consistent Preferential Bayesian Optimization for Food Arrangement

S. Kawamura, Takamitsu Matsubara, T. Shimmura, 2022, IEEE Robotics and Automation Letters.

Deep Koopman with Control: Spectral Analysis of Soft Robot Dynamics

Takamitsu Matsubara, B. Michael, N. Komeno, 2022, 2022 61st Annual Conference of the Society of Instrument and Control Engineers (SICE).

Bayesian Disturbance Injection: Robust Imitation Learning of Flexible Policies

Takamitsu Matsubara, Hikaru Sasaki, Hanbit Oh, 2021, 2021 IEEE International Conference on Robotics and Automation (ICRA).

User intent estimation during robot learning using physical human robot interaction primitives

Takamitsu Matsubara, Yunduan Cui, G. Paul, 2022, Autonomous Robots.

Environment-adaptive interaction primitives through visual context for human–robot motor skill learning

Takamitsu Matsubara, Kimitoshi Yamazaki, J. V. Miró, 2018, Autonomous Robots.

Goal-Aware Generative Adversarial Imitation Learning from Imperfect Demonstration for Robotic Cloth Manipulation

Takamitsu Matsubara, Yoshihisa Tsurumine, 2022, Robotics Auton. Syst..

Enforcing KL Regularization in General Tsallis Entropy Reinforcement Learning via Advantage Learning

E. Uchibe, Takamitsu Matsubara, Lingwei Zhu, 2022, ArXiv.

q-Munchausen Reinforcement Learning

E. Uchibe, Takamitsu Matsubara, Lingwei Zhu, 2022, ArXiv.

Probabilistic Pose Estimation of Deformable Linear Objects

Takamitsu Matsubara, Gavin Paul, Haifeng Han, 2018, 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE).

Learning Stylistic Dynamic Movement Primitives from multiple demonstrations

Jun Morimoto, Takamitsu Matsubara, Sang-Ho Hyon, 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Task-adaptive inertial parameter estimation of rigid-body dynamics with modeling error for model-based control using covariate shift adaptation

Takamitsu Matsubara, Hiroaki Takada, Kenji Sugimoto, 2014, 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

TDE2-MBRL: Energy-exchange Dynamics Learning with Task Decomposition for Spring-loaded Bipedal Robot Locomotion

Takamitsu Matsubara, Hirofumi Shin, Takumi Kamioka, 2022, 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids).

Sample-and-computation-efficient Probabilistic Model Predictive Control with Random Features

Takamitsu Matsubara, Yunduan Cui, Cheng-Yu Kuo, 2020, 2020 IEEE International Conference on Robotics and Automation (ICRA).

Reinforcement Learning Boat Autopilot: A Sample-efficient and Model Predictive Control based Approach

Takamitsu Matsubara, Yunduan Cui, Shigeki Osaki, 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Reinforcement Learning Ship Autopilot: Sample-efficient and Model Predictive Control-based Approach pdf

Takamitsu Matsubara, Yunduan Cui, Shigeki Osaki, 2019, ArXiv.

Learning to Acquire Whole-Body Humanoid Center of Mass Movements to Achieve Dynamic Tasks

Jun Morimoto, Jun Nakanishi, Gordon Cheng, 2008, Adv. Robotics.

Learning to acquire whole-body humanoid CoM movements to achieve dynamic tasks

Jun Morimoto, Jun Nakanishi, Gordon Cheng, 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

Real-time estimation of Human-Cloth topological relationship using depth sensor for robotic clothing assistance

Takamitsu Matsubara, Nishanth Koganti, Tomohiro Shibata, 2014, The 23rd IEEE International Symposium on Robot and Human Interactive Communication.

Estimation of Human Cloth Topological Relationship using Depth Sensor for Robotic Clothing Assistance

Takamitsu Matsubara, Nishanth Koganti, Tomohiro Shibata, 2013, AIR '13.

Reinforcement learning of a motor skill for wearing a T-shirt using topology coordinates

Takamitsu Matsubara, Masatsugu Kidode, Daisuke Shinohara, 2013, Adv. Robotics.

Reinforcement learning of clothing assistance with a dual-arm robot

Takamitsu Matsubara, Tomohiro Shibata, Akshara Rai, 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.

Learning motor skills with non-rigid materials by reinforcement learning

Takamitsu Matsubara, Masatsugu Kidode, Daisuke Shinohara, 2011, 2011 IEEE International Conference on Robotics and Biomimetics.

Exploiting Human and Robot Muscle Synergies for Human-in-the-loop Optimization of EMG-based Assistive Strategies

Jun Morimoto, Takamitsu Matsubara, Satoshi Yagi, 2019, 2019 International Conference on Robotics and Automation (ICRA).

Bilinear Modeling of EMG Signals to Extract User-Independent Features for Multiuser Myoelectric Interface

Jun Morimoto, Takamitsu Matsubara, J. Morimoto, 2013, IEEE Transactions on Biomedical Engineering.

Disturbance Injection Under Partial Automation: Robust Imitation Learning for Long-Horizon Tasks

Takamitsu Matsubara, Hikaru Sasaki, Hirotaka Tahara, 2023, IEEE Robotics and Automation Letters.

Composition Regulation by Flow Copolymerization of Methyl Methacrylate and Glycidyl Methacrylate with Free Radical Method

Takamitsu Matsubara, Tomoyuki Miyao, Hiroharu Ajiro, 2023, Macromolecular Materials and Engineering.

Deep reinforcement learning with smooth policy update: Application to robotic cloth manipulation

Takamitsu Matsubara, Yoshihisa Tsurumine, Yunduan Cui, 2019, Robotics Auton. Syst..

Dynamic Linear Bellman Combination of Optimal Policies for Solving New Tasks

Takamitsu Matsubara, Kenji Sugimoto, Takaya Asakura, 2015, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

Spatiotemporal synchronization of biped walking patterns with multiple external inputs by style–phase adaptation

Jun Morimoto, Takamitsu Matsubara, Akimasa Uchikata, 2015, Biological Cybernetics.

User intent estimation during robot learning using physical human robot interaction primitives

Takamitsu Matsubara, Yunduan Cui, G. Paul, 2022, Auton. Robots.

Kernel dynamic policy programming: Applicable reinforcement learning to robot systems with high dimensional states

Takamitsu Matsubara, Kenji Sugimoto, Yunduan Cui, 2017, Neural Networks.

Active tactile exploration with uncertainty and travel cost for fast shape estimation of unknown objects

Takamitsu Matsubara, Kotaro Shibata, Takamitsu Matsubara, 2017, Robotics Auton. Syst..

Probabilistic Active Filtering for Object Search in Clutter

Takamitsu Matsubara, James Poon, Yunduan Cui, 2019, 2019 International Conference on Robotics and Automation (ICRA).

Learning Force Control for Contact-Rich Manipulation Tasks With Rigid Position-Controlled Robots

Takamitsu Matsubara, Kensuke Harada, Shinichi Kikuchi, 2020, IEEE Robotics and Automation Letters.

Bayesian Policy Optimization for Waste Crane With Garbage Inhomogeneity

Hikaru Sasaki, Takamitsu Matsubara, Yukio Onuki, 2020, IEEE Robotics and Automation Letters.

Bayesian Optimization for Waste Crane Automation with Garbage Inhomogeneity

Takamitsu Matsubara, Hikaru Sasaki, 2022, Journal of the Robotics Society of Japan.

Learning a dynamic policy by using policy gradient: application to biped walking

Jun Morimoto, Jun Nakanishi, Takamitsu Matsubara, 2007, Syst. Comput. Jpn..

Deep reinforcement learning of event-triggered communication and control for multi-agent cooperative transport

Takamitsu Matsubara, Kazuki Shibata, Tomohiko Jimbo, 2021, 2021 IEEE International Conference on Robotics and Automation (ICRA).

Learning assistive strategies for exoskeleton robots from user-robot physical interaction

Jun Morimoto, Takamitsu Matsubara, Tatsuya Teramae, 2017, Pattern Recognit. Lett..

Learning assistive strategies from a few user-robot interactions: Model-based reinforcement learning approach

Jun Morimoto, Takamitsu Matsubara, Tatsuya Teramae, 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

Multi-step motion learning by combining learning-from-demonstration and policy-search

Takamitsu Matsubara, Kimitoshi Yamazaki, Hikaru Sasaki, 2023, Adv. Robotics.

Variational Policy Search using Sparse Gaussian Process Priors for Learning Multimodal Optimal Actions

Hikaru Sasaki, Takamitsu Matsubara, Takamitsu Matsubara, 2021, Neural Networks.

Learning Locally, Communicating Globally: Reinforcement Learning of Multi-robot Task Allocation for Cooperative Transport

Takamitsu Matsubara, T. Odashima, Kazuki Shibata, 2022, ArXiv.

Probabilistic active filtering with gaussian processes for occluded object search in clutter

Takamitsu Matsubara, Yunduan Cui, Jun’ichiro Ooga, 2020, Applied Intelligence.

Adaptive Step-size Policy Gradients with Average Reward Metric

Jun Morimoto, Takamitsu Matsubara, Tetsuro Morimura, 2010, ACML.

Motion Tablet : An Interface of Whole Body Motion Synthesis for Humanoid Robots with Dimentionality Reduction Methods

Takamitsu Matsubara, Ayato Iba, Masatsugu Kidode, 2012 .

Generative Adversarial Imitation Learning with Deep P-Network for Robotic Cloth Manipulation

Kimitoshi Yamazaki, Takamitsu Matsubara, Yoshihisa Tsurumine, 2019, 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids).

Hanging work of T-shirt in consideration of deformability and stretchability

Solvi Arnold, Kimitoshi Yamazaki, Takamitsu Matsubara, 2017, 2017 IEEE International Conference on Information and Automation (ICIA).

Learning to Shape by Grinding: Cutting-Surface-Aware Model-Based Reinforcement Learning

J. Morimoto, Takamitsu Matsubara, Takumi Hachimine, 2023, IEEE Robotics and Automation Letters.

Latent Kullback-Leibler control for dynamic imitation learning of whole-body behaviors in humanoid robots

Takamitsu Matsubara, Sang-Ho Hyon, Yuka Ariki, 2016, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids).

Binarized P-Network: Deep Reinforcement Learning of Robot Control from Raw Images on FPGA

Takamitsu Matsubara, Yoshihisa Tsurumine, Yuki Kadokawa, 2021, IEEE Robotics and Automation Letters.

Variationally Autoencoded Dynamic Policy Programming for Robotic Cloth Manipulation Planning based on Raw Images

Takamitsu Matsubara, Yoshihisa Tsurumine, 2022, 2022 IEEE/SICE International Symposium on System Integration (SII).

Tactile Perception Based on Injected Vibration in Soft Sensor

Takamitsu Matsubara, Naoto Komeno, Takamitsu Matsubara, 2021, IEEE Robotics and Automation Letters.

Kernel dynamic policy programming: Practical reinforcement learning for high-dimensional robots

Takamitsu Matsubara, Kenji Sugimoto, Yunduan Cui, 2016, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids).

Local Update Dynamic Policy Programming in reinforcement learning of pneumatic artificial muscle-driven humanoid hand control

Takamitsu Matsubara, Kenji Sugimoto, Yunduan Cui, 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).

Deep reinforcement learning of event-triggered communication and consensus-based control for distributed cooperative transport

Takamitsu Matsubara, Kazuki Shibata, Tomohiko Jimbo, 2022, Robotics Auton. Syst..

Uncertainty-Aware Contact-Safe Model-Based Reinforcement Learning

T. Asfour, Takamitsu Matsubara, Yunduan Cui, 2020, IEEE Robotics and Automation Letters.

XoR: Hybrid drive exoskeleton robot that can balance

Jun Morimoto, Takamitsu Matsubara, Mitsuo Kawato, 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

An optimal control approach for hybrid actuator system

Jun Morimoto, Takamitsu Matsubara, Tomoyuki Noda, 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.

Learning and adaptation of a Stylistic Myoelectric Interface: EMG-based robotic control with individual user differences

Jun Morimoto, Takamitsu Matsubara, Sang-Ho Hyon, 2011, 2011 IEEE International Conference on Robotics and Biomimetics.

Latent Kullback Leibler Control for Continuous-State Systems using Probabilistic Graphical Models

Takamitsu Matsubara, Vicenç Gómez, Hilbert J. Kappen, 2014, UAI.

Contact-based in-hand pose estimation using Bayesian state estimation and particle filtering

Takamitsu Matsubara, Felix Von Drigalski, Kazutoshi Tanaka, 2020, 2020 IEEE International Conference on Robotics and Automation (ICRA).

Bayesian Disturbance Injection: Robust Imitation Learning of Flexible Policies for Robot Manipulation

Takamitsu Matsubara, Hikaru Sasaki, Hanbit Oh, 2022, Neural Networks.

Cyclic Policy Distillation: Sample-Efficient Sim-to-Real Reinforcement Learning with Domain Randomization

Takamitsu Matsubara, Lingwei Zhu, Y. Kadokawa, 2022, Robotics Auton. Syst..

Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning

Takamitsu Matsubara, Lingwei Zhu, Toshinori Kitamura, 2021, Asian Conference on Machine Learning.

Cautious Policy Programming: Exploiting KL Regularization in Monotonic Policy Improvement for Reinforcement Learning pdf

Takamitsu Matsubara, Toshinori Kitamura, Lingwei Zhu, 2021, ArXiv.

Input-Output Manifold Learning with State Space Models

Takamitsu Matsubara, Kenji Sugimoto, Daisuke Tanaka, 2016, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

Deep Segmented DMP Networks for Learning Discontinuous Motions

Takamitsu Matsubara, Hirotaka Tahara, N. Komeno, 2023, 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE).

Environment-adaptive interaction primitives through visual context for human–robot motor skill learning

Kimitoshi Yamazaki, Jaime Valls Miró, Takamitsu Matsubara, 2018, Auton. Robots.

Environment-adaptive interaction primitives for human-robot motor skill learning

Kimitoshi Yamazaki, Jaime Valls Miró, Takamitsu Matsubara, 2016, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids).

Generalized Munchausen Reinforcement Learning using Tsallis KL Divergence

Martha White, Takamitsu Matsubara, Lingwei Zhu, 2023, 2301.11476.

Generalized Munchausen Reinforcement Learning using Tsallis KL Divergence

Takamitsu Matsubara, Zheng Chen, Lingwei Zhu, 2023, ArXiv.

Biomechanical Energy Harvester with Continuously Variable Transmission: Prototyping and Preliminary Evaluation

Takamitsu Matsubara, Taisuke Kobayashi, Yutaro Ikawa, 2018, 2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM).

Alleviating parameter-tuning burden in reinforcement learning for large-scale process control

Takamitsu Matsubara, Lingwei Zhu, G. Takami, 2022, Comput. Chem. Eng..

Scalable reinforcement learning for plant-wide control of vinyl acetate monomer process

Takamitsu Matsubara, Yunduan Cui, Go Takami, 2020 .

Factorial Kernel Dynamic Policy Programming for Vinyl Acetate Monomer Plant Model Control

Takamitsu Matsubara, Yunduan Cui, Lingwei Zhu, 2018, 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE).

Learning Stepping Motions for Fall Avoidance with Reinforcement Learning

Jun Morimoto, Takamitsu Matsubara, Joshua G. Hale, 2009 .

Data-efficient human training of a care motion controller for human transfer assistant robots using Bayesian optimization

Takamitsu Matsubara, Tsukasa Ogasawara, Kenji Sugimoto, 2016, 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob).

Policy Optimization for Waste Crane Automation From Human Preferences

Takamitsu Matsubara, Hikaru Sasaki, T. Hirabayashi, 2023, IEEE Access.

Policy Transfer from Simulations to Real World by Transfer Component Analysis

Takamitsu Matsubara, Yunduan Cui, Yuto Ozawa, 2018, 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE).