橋本和宗@大阪大学 HP

Submitted papers

S. Kanai, T. Yoshida, H. Takahashi, H. Kuroki, K. Hashimoto : Test-Time Alignment of LLMs via Sampling-Based Optimal Control in pre-logit space, [arxiv]
Y. Sawada, M. Minamide, Y. Yan, K. Hashimoto, L. Duc : Data-driven Exploration of Tropical Cyclone's Controllability [arxiv]
W. Hashimoto, K. Hashimoto: MM-LMPC: Multi-Modal Learning Model Predictive Control via Bandit-Based Mode Selection [arxiv]
W. Hashimoto, K. Hashimoto, M. Kishida, S. Takai: Reference-Free Iterative Learning Model Predictive Control with Neural Certificates [arxiv]
K. Serizawa, K. Hashimoto, W. Hashimoto, M. Kishida, S. Takai: Clustering-based Recurrent Neural Network Controller synthesis under Signal Temporal Logic Specifications [arxiv]
K. Hashimoto, Y. Yokokawa, N. Arai, X. Shen, X. Zhang, P. Raksincharoensak: Signal Temporal Logic-Based Neural Network for Driving Task Generation in Advanced Driver Assistance Systems [Preprint]

Journal Article

Y. Yuyue, Y. Maojiao, W. Yuhu and K. Hashimoto : Social Welfare Maximization in Noncooperative Dynamical Systems With Privacy-Preserving Incentive Mechanism, IEEE Transactions on Automatic Control (to appear)
K. Serizawa, K. Temma, K. Yano, A. Mehbodniya, J. Webber, T. Sakano, and K. Hashimoto : Link Availability Prediction Framework for Sub-Terahertz Wireless LANs Based on Multi-Band Propagation Information, IEEE Access, 2025 [Link]
Y. Takayama, K. Hashimoto, T. Ohtsuka: STLCCP: An Efficient Convex Optimization-based Framework for Signal Temporal Logic Specifications, IEEE Transactions on Automatic Control (accepted, 2025), [arxiv]
K. Rani, N. Ozaki, K. Hashimoto, R. Kodama, Y. Miyake, H. Nakamura, and H. Nagatomo : Predicting laser-induced surface modifications on metals in laser surface processing using a hybrid deep learning approach, Optics Continuum, 2025.
K. Hashimoto, Y. Onoue, A. Wachi, X. Shen: Learning-based Event-triggered MPC with Gaussian processes under terminal constraints, IEEE Transactions on Cybernetics (2025) [Link] [arxiv]
X. Shen, Y. Wang, K. Hashimoto, Y. Wu, S. Gros : Probabilistic reachable sets of stochastic nonlinear systems with contextual uncertainties, Automatica (2025) [Link]
W. Hashimoto, K. Hashimoto, M. Kishida, S. Takai : Robust Learning-Based Iterative Model Predictive Control for Unknown Non-Linear Systems, IET Control Theory and Applications (2024) [Link]
保津，橋本，高井：Informed RRT*アルゴリズムを用いた月極域における水探査のための経路計画手法，計測自動制御学会論文誌（2024）
二川，橋本，芹澤，高井：クラスタリングを用いたニューラル制御器の学習，システム制御情報学会論文誌（2024）
S. Patil, K. Hashimoto, M. Kishida : Robust Traffic Flow Control using Connected Vehicle Technology: Signal Spatio-Temporal Logic-based Approach, IEEE Transactions on Intelligent Transportation Systems (2024) [Link]
K. Hashimoto: Periodic event-triggered design with Bayesian optimization: an emulation-based approach, IFAC Journal of Systems and Control (2024)
W Hashimoto, K Hashimoto, A Wachi, X Shen, M Kishida, S Takai : Bayesian Meta-Learning on Control Barrier Functions with Data from On-Board Sensors, Advanced Robotics (2024) [arxiv]
X. Shen, O. Tinghui, K. Hashimoto, Y. Wu : Sample-Based Continuous Approximate Method for Constructing Interval Neural Network, IEEE Transactions on Neural Networks and Learning Systems (2024) [Link]
W. Zhijun, K. Hashimoto, W. Hashimoto, S. Takai: A Lifting Approach to Learning-Based Self-Triggered Control with Gaussian Processes, Advanced Robotics (2024) [arxiv]
L. Ding, K. Hashimoto, S. Takai: Synthesis of event-triggered controllers for SIRS epidemic models, Nonlinear Analysis: Hybrid Systems (2024) [link]
X. Shen, Y. Zhang, X. Zhang, P. Raksincharoensak and K. Hashimoto, "Robust Optimal Braking Policy for Avoiding Collision With Front Bicycle," IEEE Open Journal of Intelligent Transportation Systems (2023) [link]
森，橋本，井上：月極域における水探査のための観測機器のモデル化および日照領域の時変性を考慮した経路設計手法，日本機械学会論文集（2023）
K. Rani, N. Ozaki, Y. Hironaka, K. Hashimoto, R. Kodama, Kanji Mukai, Hirotaka Nakamura, Shigemasa Takai, and Hideo Nagatomo: Prediction of superimposed laser shot number for copper using deep convolutional neural network, Optics Express, Vol. 31, No. 15/17, pp. 24045-24053, 2023.
K. Hashimoto, A. Saoud, M. Kishida, T. Ushio, D. V. Dimarogonas: Learning-based symbolic abstractions for nonlinear control systems, Automatica (full paper, 2022) [arxiv]
W. Hashimoto, K. Hashimoto, S. Takai: STL2vec: Signal Temporal Logic Embeddings for Control Synthesis With Recurrent Neural Networks, IEEE Robotics & Automation Letters, vol. 7, no. 2, pp. 5246-5253 (2022, JST CREST の支援) [link] [arxiv] [JST Press Release]
K. Hashimoto, N. Tsumagari, T. Ushio: Collaborative rover-copter path planning and exploration with temporal logic specifications based on Bayesian update under uncertain environments, ACM Transactions on Cyber Physical Systems, vol. 6, no. 2, pp. 1-24 (2022) [link] [arxiv]
K. Hashimoto*, Y. Onoue*, M. Ogura, T. Ushio: Event-triggered control for mitigating SIS spreading processes, Annual Reviews in Control, vol. 52, pp. 479-494 (2021) [link] [arxiv]
K. Hashimoto, Y. Yoshimura, T. Ushio: “Learning self-triggered controllers with Gaussian processes”, IEEE Transactions on Cybernetics, vol. 51, no. 12, pp. 6294-6304 (2021) [link]
K. Hashimoto, M. Kishida, Y. Yoshimura, T. Ushio: A Bayesian optimization approach to decentralized event-triggered control, IEICE Transactions on Fundamentals, Vol. E 104-A, No. 2, pp. 447-454 (2021) [link]
吉村優一, 橋本和宗, 潮俊光: "ガウス過程を用いた事象駆動型制御器の設計", システム制御情報学会論文誌, Vol. 33, No. 7, pp. 219-228 (2020)
K. Hashimoto, M. Chong, and D. V. Dimarogonas: “Distributed L1 state-and-fault estimation for multi-agent systems”, IEEE Transactions on Control of Network Systems, Vol.7, No.2, pp 699-710 (2020) [link]
K. Hashimoto and D. V. Dimarogonas: “Synthesizing communication plans for reachability and safety specifications”, IEEE Transactions on Automatic Control, Vol.65, No.2, pp.561-576 (2020) [link]
K. Hashimoto and D. V. Dimarogonas: “Resource-aware networked control systems under temporal logic specifications”, Discrete Event Dynamic Systems, Vol. 29, No. 4, pp. 473-499 (2019) [link]
K. Hashimoto, A. Saoud, M. Kishida, T. Ushio, and D. V. Dimarogonas: “A symbolic approach to the self-triggered design for networked control systems”, IEEE Control Systems Letters, Vol. 3, No. 4, pp. 1050-1055 (2019) [link]
八田羽謙一，橋本和宗，井上正樹，足立修一，上野将樹，堤優二郎，山田輝樹，豊嶋弘和: “不確かさをもつターボチャージシステムの可到達解析と安全性検証法”, 自動車技術会論文集, Vol. 50, No. 3, pp. 957-962 (2019)
M. Hirano*, K. Hashimoto*, F. Nakagawa, T. Ido, Y. Hanado, and S. Adachi: “State estimation for multiple clocks under anomalies using L1-norm optimization”, Metrologia, Vol. 56, No.2 (2019) [link]
K. Hashimoto, S. Adachi, D. V. Dimarogonas: “Aperiodic sampled-data control via explicit transmission mapping: a set-invariance approach”, IEEE Transactions on Automatic Control, Vol. 63, No. 10, pp. 3523-3530 (2018) [link]
K. Hashimoto, S. Adachi, D. V. Dimarogonas: “Self-triggered model predictive control for nonlinear input-affine dynamical systems via adaptive control samples selection”, IEEE Transactions on Automatic Control, Vol. 62, No. 1, pp. 177-189, (2017) [link]
K. Hashimoto, S. Adachi, D. V. Dimarogonas: “Event-triggered intermittent sampling for nonlinear model predictive control”, Automatica, Vol. 81, pp. 148-155 (2017) [link]
K. Hashimoto, S. Adachi, D. V. Dimarogonas: “Distributed aperiodic model predictive control for multi-agent systems”, IET Control Theory and Applications, Vol. 9, No. 1, pp. 10-20 (2015) [link]

(the symbol " * " means equal contribution)

International Conference (Only Full paper, Peer reviewed)

X. Shen, A. Wachi, W. Hashimoto, K. Hashimoto, S. Takai : Safe Reinforcement Learning Using Model Predictive Control with Probabilistic Control Barrier Function, American Control Conference (2024)
A Wachi, W Hashimoto, K Hashimoto : Long-term Safe Reinforcement Learning with Binary Feedback, Association for the Advancement of Artificial Intelligence (AAAI), 2024
A. Wachi, W. Hashimoto, X. Shen, K. Hashimoto: Safe Exploration in Reinforcement Learning: A Generalized Formulation and Algorithms, Neural Information Processing Systems (NeurIPS), 2023
Y. Takayama, K. Hashimoto, T. Ohtsuka: Signal Temporal Logic Meets Convex-Concave Programming: A Structure-Exploiting SQP Algorithm for STL Specifications, IEEE International Conference on Decision and Control (IEEE CDC), 2023
S. Patil, K. Hashimoto, M. Kishida: Traffic Flow Control at Signalized Intersections Using Signal Spatio-Temporal Logic, IEEE International Conference on Decision and Control (IEEE CDC), 2022
W. Hashimoto, K. Hashimoto, S. Takai: STL2vec: Signal Temporal Logic Embeddings for Control Synthesis With Recurrent Neural Networks, IEEE International Conference on Robotics and Automation (ICRA), 2022 (its journal version has appeared in IEEE RAL)
W. Hashimoto, K. Hashimoto, Y. Onoue, S. Takai: Learning-Based Iterative Optimal Control for Unknown Systems Using Gaussian Process Regression, European Control Conference (ECC), 2022
Y. Mori，K. Hashimoto, and H. Inoue, “Path planning for Lunar polar exploration: Bayesian network-based sensor modeling of neutron spectrometers and sampling-based optimal motion planning,” AIAA Science and Technology Forum and Exposition (2022 AIAA SciTech Forum), Hybrid format January 2022
K. Hashimoto, “Safe and active parameter exploration for event-triggered control”, in Proceedings of the 16th IEEE International Conference on Control & Automation (ICCA), presented online, pp. 19-24, October, 2020 (Best paper award finalist).
T. Kinugawa, K. Hashimoto and T. Ushio, “Control of timed discrete event systems with ticked linear temporal logic constraints”, in Proceedings of the 21st IFAC World Congress, presented online, pp. 2173-2178, July, 2020.
Y. Kikuchi, H. Inoue, K. Hashimoto and S. Adachi, “Path Planning for Lunar Polar Exploration Mission Using Linear Temporal Logic”, in Proceedings of 2020 AIAA SciTech Forum, Orland, Florida, USA, pp. 1-9, January, 2020.
K. Hashimoto, A. Saoud, M. Kishida, T. Ushio, and D. V. Dimarogonas: “A symbolic approach to the self-triggered design for networked control systems”, In Proceedings of 58th IEEE Conference on Decision and Control (IEEE CDC), Nice, France, December 2019 (Its Journal version appeared in IEEE Control Systems Letters).
K. Hashimoto, M. S. Chong, and D. V. Dimarogonas, “Realtime L1-fault-and-state estimation for multi-agent systems”, in Proceedings of 2019 American Control Conference (ACC), pp. 1175-1180, Philadelphia, USA, May, 2019.
K. Hashimoto, S. Adachi, and D. V. Dimarogonas, “Energy-aware networked control systems under temporal logic specifications”, In Proceedings of 57th IEEE Conference on Decision and Control (IEEE CDC), pp. 132-139, Miami Beach, USA, December 2018 （2019年度計測自動制御学会関西支部支部長賞）.
K. Hashimoto, S. Adachi, and D. V. Dimarogonas, “Self-triggered control for constrained systems:a contractive set-based approach”, in Proceedings of 2017 American Control Conference (ACC), pp. 1011-1016, Seattle, USA, July, 2017.
K. Hashimoto, S. Adachi, and D. V. Dimarogonas, “Robust safety controller synthesis using tubes”, in Proceedings of the 56th IEEE Conference on Decision and Control (IEEE CDC), pp. 535-541, Melbourne, Australia, December, 2017.
K. Hashimoto, S. Adachi, and D. V. Dimarogonas,，“A collision-free communication scheduling for nonlinear model predictive control”, in Proceedings of the 20th IFAC World Congress, pp. 8939-8944, Toulouse, France, July, 2017.
K. Hashimoto, S. Adachi, and D. V. Dimarogonas, “Self-triggered model predictive control for continuous-time systems: A multiple discretizations approach”, in Proceedings of the 55th IEEE Conference on Decision and Control (IEEE CDC), pp. 3078-3083, Las Vegas, USA, December, 2016.
K. Hashimoto, S. Adachi, and D. V. Dimarogonas, “Time-constrained event-triggered model predictive control for nonlinear continuous-time systems”, in Proceedings of the 54th IEEE Conference on Decision and Control (IEEE CDC), pp. 4326-4331, Osaka, Japan, December, 2015.
K. Hashimoto, S. Adachi, and D. V. Dimarogonas, “Self-triggered nonlinear model predictive control for networked control systems”, in Proceedings of American Control Conference (ACC), pp. 4329-4244, Chicago, USA, May, 2015.
K. Hashimoto, S. Adachi, and D. V. Dimarogonas, “Distributed event-based model predictive control for multi-agent systems under disturbances”, International conference on Network Games, Control, and Optimization (NetGCooP), pp. 255-261, Trento, Italy, October, 2014.

Invited talks, Seminars, Commentary articles

橋本和宗：ガウス過程回帰による自己駆動型制御器の設計，計測と制御，特集：IoT時代に向けたイベントベースト制御，解説，vol. 60, no. 1，2021年1月．
橋本和宗：ガウス過程による自己駆動型制御器の設計，第62回自動制御連合講演会，札幌コンベンションセンター，北海道，2019年11月．
橋本和宗：ガウス過程を用いたネットワーク化制御システムにおける自己駆動型制御器の設計，真なるダイナミクスの追求によるシステム制御理論の躍進を目指すシンポジウム，霧島国際ホテル，鹿児島，2019年10月．
橋本和宗：ネットワーク化制御システムのための制御系設計：事象駆動制御と自己駆動制御，足立研セミナー，慶應義塾大学矢上キャンパス，2019年8月．

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