| Contraction theory for nonlinear stability analysis and learning-based control: A tutorial overview H Tsukamoto, SJ Chung, JJE Slotine Annual Reviews in Control 52, 135-169, 2021 | 130 | 2021 |
| Neural Contraction Metrics for Robust Estimation and Control: A Convex Optimization Approach H Tsukamoto, SJ Chung IEEE Control Systems Letters (L-CSS) 5 (1), pp. 211-216, 2021 | 71 | 2021 |
| Robust Controller Design for Stochastic Nonlinear Systems via Convex Optimization H Tsukamoto, SJ Chung IEEE Transactions on Automatic Control (Early Access), 2020 | 53 | 2020 |
| Neural Stochastic Contraction Metrics for Learning-based Control and Estimation H Tsukamoto, SJ Chung, JJE Slotine IEEE Control Systems Letters (L-CSS), Preprint Version, 2020 | 46 | 2020 |
| Learning-based robust motion planning with guaranteed stability: A contraction theory approach H Tsukamoto, SJ Chung IEEE Robotics and Automation Letters 6 (4), 6164-6171, 2021 | 35 | 2021 |
| Learning-based adaptive control using contraction theory H Tsukamoto, SJ Chung, JJ Slotine 2021 60th IEEE conference on decision and control (CDC), 2533-2538, 2021 | 21 | 2021 |
| Safe motion planning with tubes and contraction metrics S Singh, H Tsukamoto, BT Lopez, SJ Chung, JJ Slotine 2021 60th IEEE Conference on Decision and Control (CDC), 2943-2948, 2021 | 15 | 2021 |
| Convex Optimization-based Controller Design for Stochastic Nonlinear Systems using Contraction Analysis H Tsukamoto, SJ Chung 58th IEEE Conference on Decision and Control (CDC), pp. 8196–8203, 2019 | 15 | 2019 |
| Learning-based adaptive control via contraction theory H Tsukamoto, SJ Chung, JJ Slotine IEEE CDC, 2021 | 12 | 2021 |
| A theoretical overview of neural contraction metrics for learning-based control with guaranteed stability H Tsukamoto, SJ Chung, JJ Slotine, C Fan 2021 60th IEEE Conference on Decision and Control (CDC), 2949-2954, 2021 | 7 | 2021 |
| Interstellar object accessibility and mission design BPS Donitz, D Mages, H Tsukamoto, P Dixon, D Landau, SJ Chung, ... 2023 IEEE Aerospace Conference, 1-9, 2023 | 4 | 2023 |
| Neural-rendezvous: Learning-based robust guidance and control to encounter interstellar objects H Tsukamoto, SJ Chung, B Donitz, M Ingham, D Mages, YK Nakka AIAA Journal of Guidance, Control, and Dynamics, under review, 2022 | 3 | 2022 |
| Imitation learning for robust and safe online motion planning: A contraction theory approach H Tsukamoto, SJ Chung Submitted to IEEE Robot. Automat. Lett, 2021 | 2 | 2021 |
| Robust Optimal Network Topology Switching for Zero Dynamics Attacks H Tsukamoto, JD Ibrahim, J Hajar, J Ragan, SJ Chung, FY Hadaegh arXiv preprint arXiv:2407.18440, 2024 | 1 | 2024 |
| Regret-Optimal Defense Against Stealthy Adversaries: A System Level Approach H Tsukamoto, J Hajar, SJ Chung, FY Hadaegh arXiv preprint arXiv:2407.18448, 2024 | 1 | 2024 |
| CaRT: Certified Safety and Robust Tracking in Learning-Based Motion Planning for Multi-Agent Systems H Tsukamoto, B Rivière, C Choi, A Rahmani, SJ Chung 2023 62nd IEEE Conference on Decision and Control (CDC), 2910-2917, 2023 | 1 | 2023 |
| CART: Collision avoidance and robust tracking augmentation in learning-based motion planning for multi-agent systems H Tsukamoto, B Rivière, C Choi, A Rahmani, SJ Chung IEEE Conf. Decis. Control, under review, 2023 | 1 | 2023 |
| Contraction Theory for Robust Learning-Based Control: Toward Aerospace and Robotic Autonomy H Tsukamoto California Institute of Technology, 2023 | 1 | 2023 |
| Neural-Rendezvous: Provably Robust Guidance and Control to Encounter Interstellar Objects H Tsukamoto, SJ Chung, YK Nakka, B Donitz, D Mages, M Ingham Journal of Guidance, Control, and Dynamics 47 (12), 2525-2543, 2024 | | 2024 |
| Information-Optimal Multi-Spacecraft Positioning for Interstellar Object Exploration A Bhardwaj, S Bhatta, H Tsukamoto arXiv preprint arXiv:2411.09110, 2024 | | 2024 |
Soon-Jo ChungBren Professor of Control and Dynamical Systems at Caltech; JPL Senior Research ScientistDirección de correo verificada de caltech.edu
