森本　淳 Jun Morimoto

[2025]

• Satoshi Yagi, Jun Morimoto (2025), Learning-Based Joint Control With Hierarchical Reinforcement Learning and On-Device Execution. IEEE Robotics Automation Letters, 10(12), pp. 12493-12500. [Open Access]

• Jun-ichiro Furukawa, Jun Morimoto (2025), Transformer-based multitask assist control from first-person view image and user’s kinematic information for exoskeleton robots, npj Robotics, 3(13). [Open Access]

• Takumi Hachimine, Jun Morimoto, Takamitsu Matsubara (2025),
  Cutting Sequence Diffuser: Sim-to-Real Transferable Planning for Object Shaping by Grinding. IEEE Robotics Automation Letters, 10(2), pp. 1162-1169.

• Asuka Takai, Mitsuo Kawato, Jun Morimoto, Marco Santello, et al. (2025),
  Role specialization enables superior task performance by human dyads than individuals,
  The International Journal of Robotics Research, First published online. [Open Access]

• Satoshi Yamamori, Jun Morimoto (2025), Phase-amplitude reduction-based imitation learning, Advanced Robotics, 39(3), pp. 156-170. [Open Access]

• Satoshi Yamamori, Jun Morimoto (2025), Foundational Policy Acquisition via Multitask Learning for Motor Skill Generation, IEEE Transactions on Cognitive and Developmental Systems, 17(5), pp. 1260-1271. [Open Access]

• Tatsuya Teramae, Takamitsu Matsubara, Tomoyuki Noda, Jun Morimoto (2025),
  Optimizing non-assisted body part movements for robot-assisted therapy. Biomedical Signal Processing and Control, 107, 107817. [Open Access]

• Tatsuya Teramae, Takamitsu Matsubara, Tomoyuki Noda, Jun Morimoto (2025),
  Neural-enhanced motion-to-EMG: refining simulated muscle activity from musculoskeletal models using a Seq2Seq approach, Frontiers in Bioengineering and Biotechnology, Vol. 13. [Open Access]

• Hidaka Asai, Tomoyuki Noda, Jun Morimoto (2025),
  Dynamical modeling of torso stability in running via hip–knee three pairs of six springs,
  Bioinspiration & Biomimetics, 20(6). [Open Access]

• Eisuke Matsubara, Satoshi Yagi, Yuta Goto, Satoshi Yamamori, Jun Morimoto (2025),
  Improvement of fault tolerance of quadruped robots by detecting correlation anomalies in sensor signals, Artificial Life and Robotics, 30(2), pp. 252-259.

• Sho Takeda, Satoshi Yamamori, Satoshi Yagi, Jun Morimoto (2025),
  An empirical evaluation of a hierarchical reinforcement learning method towards modular robot control, Artificial Life and Robotics, 30(2), pp. 245-251.

[2024]

• Hidaka Asai, Tomoyuki Noda, Tatsuya Teramae, Jun Morimoto (2024), Modeling Inverse Airflow Dynamics Towards Fast Movement Generation using Pneumatic Artificial Muscle with Long Air Tubes, IEEE/ASME Transactions on Mechatronics, Vol. 29(4), pp. 3038 – 3046. [Open Access]

• Chang Liu, Satoshi Yagi, Satoshi Yamamori, Jun Morimoto (2024),
  Joint-Aware Transformer: An Inter-Joint Correlation Encoding Transformer for Short-Term 3D Human Motion Prediction, IEEE Access, pp. 156683 – 156693. [Open Access].

• Matija Mavsar, Jun Morimoto, Ales Ude (2024), GAN-Based Semi-Supervised Training of LSTM Nets for Intention Recognition in Cooperative Tasks, IEEE Robotics and Automation Letters, Vol. 9(1), pp. 263 – 270. [Open Access]

• Matija Mavsar, Barry Ridge, Rok Pahic, Jun Morimoto, Ales Ude (2024), Simulation-Aided Handover Prediction From Video Using Recurrent Image-to-Motion Networks, IEEE Transactions on Neural Networks and Learning Systems, [Open Access]

[2023]

• Sunhwi Kang, Koji Ishihara, Norikazu Sugimoto, Jun Morimoto (2023), Curriculum-based humanoid robot identification using large-scale human motion database, Frontiers in Robotics and AI, doi.org/10.3389/frobt.2023.1282299, [Open Access]

• Takumi Hachimine, Jun Morimoto, Takamitsu Matsubara (2023), Learning to Shape by Grinding: Cutting-Surface-Aware Model-Based Reinforcement Learning, IEEE Robotics and Automation Letters, Volume: 8, Issue: 10, [Journal Page]

• Asuka Takai, Qiushi Fu, Yuzuru Doibata, Giuseppe Lisi, Toshiki Tsuchiya, Keivan Mojtahedi, Toshinori Yoshioka, Mitsuo Kawato, Jun Morimoto*, Marco Santello* (2023), Learning acquisition of consistent leader–follower relationships depends on implicit haptic interactions, Scientific Reports, 13, Article number: 3476, [Open Access]

• Yoko Takahashi, Tomoyuki Noda, Jun Morimoto, Michiyuki Kawakami, et al. (2023), Robotized Knee-Ankle-Foot Orthosis-Assisted Gait Training on Genu Recurvatum during Gait in Patients with Chronic Stroke: A Feasibility Study and Case Report, Journal of Clinical Medicine, 12(2), 415, [Open Access]

• Yuko Nakamura et al. (2023), Distinctive alterations in the mesocorticolimbic circuits in various psychiatric disorders, Psychiatry and Clinical Neurosciences, doi.org/10.1111/pcn.13542,
  [Open Access]

• Takuya Ishida, et al. (2023), Aberrant Large-Scale Network Interactions Across Psychiatric Disorders Revealed by Large-Sample Multi-Site Resting-State Functional Magnetic Resonance Imaging Datasets, Schizophrenia Bulletin, vol. 49 no. 4 pp. 933–943, [Open Access]

• Shinya Chiyohara, Jun-ichiro Furukawa, Tomoyuki Noda, Jun Morimoto*, Hiroshi Imamizu (2023), Proprioceptive short-term memory in passive motor learning, Scientific Reports, 13, Article number: 20826, [Open Access]

• Asuka Takai, Tatsuya Teramae, Tomoyuki Noda, Koji Ishihara, Jun-ichiro Furukawa, Hiroaki Fujimoto, Megumi Hatakenaka, Nobukazu Fujita, Akihiro Jino, Yuichi Hiramatsu, Ichiro Miyai, Jun Morimoto (2023), Development of split-force-controlled body weight support (SF-BWS) robot for gait rehabilitation, Frontiers in Human Neuroscience, doi.org/10.3389/fnhum.2023.1197380, [Open Access]

• Tomoya Yamanokuchi, Yuhwan Kwon, Yoshihisa Tsurumine, Eiji Uchibe, Jun Morimoto, Takamitsu Matsubara (2023), Randomized-to-Canonical Model Predictive Control for Real-World Visual Robotic Manipulation, IEEE Robotics and Automation Letters, [Journal Page]

[2022]

• Yutaka Matsuo, Yann LeCun, Maneesh Sahani, Doina Precup, David Silver, Masashi Sugiyama, Eiji Uchibe, Jun Morimoto (2022), Deep learning, reinforcement learning, and world models, Neural Networks, Vol. 152, pp. 267-275, [Open Access]

• Takeuchi H, Yahata N, Lisi G, Tsurumi K, Yoshihara Y, Kawada R, Murao T, Mizuta H, Yokomoto T, Miyagi T, Nakagami Y, Yoshioka T, Yoshimoto J, Kawato M, Murai T, Morimoto J, Takahashi H (2022), Development of a classifier for gambling disorder based on functional connections between brain regions, Psychiatry Clin Neurosci. 2022 Mar 13. doi: 10.1111/pcn.13350. [Open Access]

• Jun-ichiro Furukawa, Shotaro Okajima, Qi An, Yuichi Nakamura, Jun Morimoto (2022), Selective Assist Strategy by Using Lightweight Carbon Frame Exoskeleton Robot, IEEE Robotics and Automation Letters, [Open Access]

• Takeshi D. Itoh, Koji Ishihara, Jun Morimoto (2022), Implicit Contact Dynamics Modeling With Explicit Inertia Matrix Representation for Real-Time, Model-Based Control in Physical Environment, Neural Computation, [Open Access]

[2021]

• Asuka Takai, Giuseppe Lisi, Tomoyuki Noda, Tatsuya Teramae, Hiroshi Imamizu, Jun Morimoto (2021)
  Bayesian Estimation of Potential Performance Improvement Elicited by Robot-Guided Training
  Frontiers in Neurscience, fnins.2021.704402, [Open Access]

• Tom Macpherson, Masayuki Matsumoto, Hiroaki Gomi, Jun Morimoto, Eiji Uchibe, Takatoshi Hikida (2021)
  Parallel and hierarchical neural mechanisms for adaptive and predictive behavioral control,
  Neural Networks, Vol. 144, pp. 507-521, [Open Access]

• Saori C. Tanaka, et al. (2021), A multi-site, multi-disorder resting-state magnetic resonance image database, Scientific Data, 8, Article number: 227 [Open Access]

• Jun-ichiro Furukawa, Shinya Chiyohara, Tatsuya Teramae, Asuka Takai, Jun Morimoto (2021), A Collaborative Filtering Approach Toward Plug-and-Play Myoelectric Robot Control, IEEE Transactions on Human-Machine Systems, Vol. 51, Issue 5, 514-523. [Open Access]

• Jun-ichiro Furukawa, Jun Morimoto (2021), Composing an Assistive Control Strategy Based on Linear Bellman Combination From Estimated User’s Motor Goal, IEEE Robotics and Automation Letters, Vol. 6, Issue: 2, pp. 1051 – 1058. [Open Access]

• Prevoius papers can be found in [this page]

[2026]
• [New!] Chang Liu,Qinchao Xu, Satoshi Yagi, Satoshi Yamamori, Yaonan Zhu, Yusuke Iwasawa,
  Kazuya Yoshida, Jun Morimoto (2026),
  M2oE: Modular Mixture of Experts for Multi-Morphology Reinforcement Learning of Modular Robots,
  IEEE International Conference on Robotics and Automation (ICRA 2026), accepted.

• [New!] Qinchao Xu, Satoshi Yagi, Satoshi Yamamori, Jun Morimoto (2026),
  When the Adversary Knows You Better: Adversarial Training for Learning-Based Legged Robots,
  IEEE International Conference on Robotics and Automation (ICRA 2026), accepted.

• [New!] Kenjiro Minamikawa, Satoshi Yamamori, Satoshi Yagi, Sho Takeda, Kazuya Yoshida, Jun Morimoto (2026),
  Motion Generation for Modular Robots Using Hierarchical Policies,
  IEEE International Conference on Robotics and Automation (ICRA 2026), accepted.

[2025]

• Ruixiang Cao, Satoshi Yagi, Satoshi Yamamori, Jun Morimoto (2025),
  VecNav: Vector Goal Robot Navigation from In-the-wild Videos,
  IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2025) 17207-17214.

• Kai Tsunoda, Satoshi Yagi, Satoshi Yamamori, Jun Morimoto (2025),
  Generating Velocity-Adaptive Manipulation Through Learning from Human Movement Speed Variations, IEEE-RAS 24th International Conference on Humanoid Robots (Humanoids 2025), 712-719

• Yuta Goto, Satoshi Yamamori, Satoshi Yagi, and Jun Morimoto (2025),
  Parameter-Space Policy Composition for Sim-to-Real Transfer in Quadruped Locomotion Control,
  32nd International Conference on Neural Information Processing (ICONIP 2025),
  https://doi.org/10.1007/978-981-95-4445-5_26

• Jin Shi, Satoshi Yagi, Satoshi Yamamori, Jun Morimoto (2025),
  LLM-Guided Zero-Shot Visual Object Navigation with Building Semantic Map,
  IEEE/SICE International Symposium on System Integrations (SII 2025), 1274-1279.

[-2024]

[TBA]

[TBA]

解説論文：

・古川　淳一郎，森本　淳　(2025)
　一人称視点映像と運動情報を用いたTransformerに基づく装着型運動アシストロボットのマルチタスク制御
　ロボット（日本ロボット工業会），No. 286, pp. 45 – 47[新技術], 2025.

・古川　淳一郎，森本　淳　(2024)
　外骨格ロボットの運動学習手法（「AI時代の物理的ヒューマン・ロボットインタラクション」特集）
　日本ロボット学会誌，Vol. 42, No. 10, pp. 947 – 952, 2024.

・石原　弘二，森本　淳　(2021) （「強化学習最先端とロボティクス」特集）
　全身のダイナミクスを考慮した最適制御
　日本ロボット学会誌, Vol.39, No. 7, pp. 29-32, 2021.

・濱屋　政志，松原　崇充，森本　淳　(2018)
　外骨格ロボットに搭載された空気圧人工筋の協調同定ーガウス過程に基づく能動学習のアプローチ
　システム／制御／情報, Vol.62, No.10, pp. 423-428, 2018.

・森本　淳　(2018)
　ヒト動作の模倣によるヒト型ロボット動作学習
　生体の科学, Vol.69, No.1, pp. 51-53, 2018年1-2月号.

・川鍋　一晃，山下　宙人，森本　淳　(2018)
　人を理解するためのBMI技術
　情報処理 (JPSJ MAGAZINE), 2018年, 1月号.

・森本　淳, リジ・ジュゼッペ, 高井　飛鳥　(2017)
　装着型ロボットを駆動するBMI技術
　Medical Science Digest, 2017年, 9月号.

・野田　智之、寺前　達也、高井　飛鳥、長谷　公隆、森本　淳　(2017)
　普段使いの装具をロボット化：空気圧人工筋で駆動するモジュール関節付き下肢装具の開発
　MEDICAL REHABILITATION, Vol. 205, 2017.1, pp. 22-27.

・森本　淳, 八幡　憲明, 橋本　龍一郎, 川人　光男　(2015)
　rs-fcMRIを用いた精神神経疾患の判別　
　Clinical Neuroscience, Vol.33, (15年) 10月号.

・森本　淳, 八幡　憲明, 橋本　龍一郎, 川人　光男　(2015)
　脳活動ビッグデータ解析による病態理解に向けた疾患判別　
　分子精神医学,　特集：計算神経科学と精神医学, Vol. 15, No. 1, pp. 2-6.

・森本　淳, 杉本徳和 (2013)
　高次元・実環境における強化学習　
　計測と制御, Vol.52, No. 8, pp. 742-748.

・森本　淳　(2013)
　ロボット制御からみた二足歩行：ヒト型ロボットの歩行制御
　MEDICAL REHABILITATION, Vol. 156, 2013.4, pp. 73-79.

・森本　淳　(2012)
　ロボット学習　
　オペレーションズ・リサーチ, Vol. 57, No. 7, pp. 367-372.

・森本　淳　(2008)
　同期メカニズムを用いた2足歩行　－人間の歩行計測とヒューマノイドロボットの歩行制御－
　日本ロボット学会誌　Vol. 26, No. 3, pp. 238-241.　

・森本　淳　(2004)
　ATR脳情報研究所
　システム／制御／情報，Vol. 48, No. 8, pp. 348-349.

・森本　淳　(2004)
　「ロボットの運動学習」特集について
　日本ロボット学会誌, Vol. 22, No. 2, pp. 1, 43.

・銅谷　賢治，森本　淳，鮫島　和行　(2001)
　強化学習と最適制御
　システム／制御／情報，Vol. 45, No. 4, pp. 186-196.

・森本　淳，銅谷　賢治　(2001)
　階層型強化学習を用いた３リンク２関節ロボットによる起立運動の獲得
　日本ロボット学会誌 vol. 19, No. 5, pp574-579.

国内論文誌：

・松原　崇充, 森本　淳 (2013)
　多重時系列データ解析のための正準多重整列法
　電子情報通信学会論文誌 Vol. J96-D, No.2, pp.298-305

・内方　章雅, 松原　崇充, 森本　淳 (2012)
　スタイル-位相適応に基づく周期運動の時空間同期：２足歩行運動への適用
　電子情報通信学会論文誌　Vol. J95-D, No. 7, pp. 1476-1478

・松原　崇充, 玄　相昊, 森本　淳 (2011)
　個性を考慮した周期的全身運動の予測
　電子情報通信学会論文誌　Vol. J94-D, No. 1, pp. 344-355

・丸山　淳一，松原　崇充，Josua G. Hale，森本　淳 (2009)
　強化学習を用いたヒューマノイドロボットによる転倒回避ステップ動作の学習
　日本ロボット学会誌，Vol. 27，No. 5，pp. 527-537

・有木　由香，森本　淳，玄　相昊　(2008)
　動作認識における床反力情報の推定と見まね学習への適用
　電子情報通信学会論文誌　Vol. J91-D, No. 9, pp. 2394-2403

・松原崇充，森本　淳，中西　淳，佐藤雅昭，銅谷賢治　(2005)
　方策勾配法を用いた動的行動則の獲得：２足歩行への適用
　電子情報通信学会論文誌　Vol. J88-D2, No. 1, pp. 53-65.

・宮本　弘之，森本　淳，銅谷　賢治，川人　光男 (1999)
　経由点表現を用いた強化学習
　電子情報通信学会論文誌　Vol. J82-D2, No 11, pp. 2111-2117.

・森本　淳，銅谷　賢治　(1999)
　強化学習を用いた高次元連続状態空間における系列運動学習
　電子情報通信学会論文誌　vol. J82-D2, no 11, pp. 2118-2131.

紀要：

・森本 淳　(2007)
　計算論的神経科学とロボティクス
　北野病院紀要　第51巻・第52巻合併号, pp. 1-12, 2007

[TBA]

[TBA]