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Hiroyasu Tsukamoto
Hiroyasu Tsukamoto
Incoming Assistant Professor of Aerospace, University of Illinois Urbana-Champaign/NASA JPL
Verified email at caltech.edu - Homepage
Title
Cited by
Cited by
Year
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
912021
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
612021
Robust Controller Design for Stochastic Nonlinear Systems via Convex Optimization
H Tsukamoto, SJ Chung
IEEE Transactions on Automatic Control (Early Access), 2020
462020
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
432020
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
262021
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
162021
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
132019
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
112021
Learning-based adaptive control via contraction theory
H Tsukamoto, SJ Chung, JJ Slotine
IEEE CDC, 2021
112021
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
92021
Neural-rendezvous: Learning-based robust guidance and control to encounter interstellar objects
H Tsukamoto, SJ Chung, B Donitz, M Ingham, D Mages, YK Nakka
arXiv preprint arXiv:2208.04883, 2022
32022
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
22023
Imitation learning for robust and safe online motion planning: A contraction theory approach
H Tsukamoto, SJ Chung
Submitted to IEEE Robot. Automat. Lett, 2021
22021
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
arXiv preprint arXiv:2307.08602, 2023
12023
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
2023
Contraction Theory for Robust Learning-Based Control: Toward Aerospace and Robotic Autonomy
H Tsukamoto
California Institute of Technology, 2023
2023
Imitation Learning for Robust and Safe Real-time Motion Planning: A Contraction Theory Approach.
H Tsukamoto, SJ Chung
CoRR, 2021
2021
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