Hiroyasu Tsukamoto

According to our database, Hiroyasu Tsukamoto authored at least 18 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Regret-Optimal Defense Against Stealthy Adversaries: A System Level Approach.

Hiroyasu Tsukamoto, Joudi Hajar, Soon-Jo Chung, Fred Y. Hadaegh

CoRR, 2024

Robust Optimal Network Topology Switching for Zero Dynamics Attacks.

Hiroyasu Tsukamoto, Joshua D. Ibrahim, Joudi Hajar, James Ragan, Soon-Jo Chung, Fred Y. Hadaegh

CoRR, 2024

2023

CART: Collision Avoidance and Robust Tracking Augmentation in Learning-based Motion Planning for Multi-Agent Systems.

Hiroyasu Tsukamoto, Benjamin Rivière, Changrak Choi, Amir Rahmani, Soon-Jo Chung

CoRR, 2023

CaRT: Certified Safety and Robust Tracking in Learning-Based Motion Planning for Multi-Agent Systems.

Hiroyasu Tsukamoto, Benjamin Rivière, Changrak Choi, Amir Rahmani, Soon-Jo Chung

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

Interstellar Object Accessibility and Mission Design.

Benjamin P. S. Donitz, Declan Mages, Hiroyasu Tsukamoto, Peter Dixon, Damon Landau, Soon-Jo Chung, Erica Bufanda, Michel D. Ingham, Julie C. Castillo-Rogez

CoRR, 2022

Neural-Rendezvous: Learning-based Robust Guidance and Control to Encounter Interstellar Objects.

Hiroyasu Tsukamoto, Soon-Jo Chung, Benjamin Donitz, Michel D. Ingham, Declan Mages, Yashwanth Kumar Nakka

CoRR, 2022

2021

Robust Controller Design for Stochastic Nonlinear Systems via Convex Optimization.

Hiroyasu Tsukamoto, Soon-Jo Chung

IEEE Trans. Autom. Control., 2021

Learning-based Robust Motion Planning With Guaranteed Stability: A Contraction Theory Approach.

Hiroyasu Tsukamoto, Soon-Jo Chung

IEEE Robotics Autom. Lett., 2021

Neural Stochastic Contraction Metrics for Learning-Based Control and Estimation.

Hiroyasu Tsukamoto, Soon-Jo Chung, Jean-Jacques E. Slotine

IEEE Control. Syst. Lett., 2021

Neural Contraction Metrics for Robust Estimation and Control: A Convex Optimization Approach.

Hiroyasu Tsukamoto, Soon-Jo Chung

IEEE Control. Syst. Lett., 2021

Learning-based Adaptive Control via Contraction Theory.

Hiroyasu Tsukamoto, Soon-Jo Chung, Jean-Jacques E. Slotine

CoRR, 2021

Imitation Learning for Robust and Safe Real-time Motion Planning: A Contraction Theory Approach.

Hiroyasu Tsukamoto, Soon-Jo Chung

CoRR, 2021

Contraction theory for nonlinear stability analysis and learning-based control: A tutorial overview.

Hiroyasu Tsukamoto, Soon-Jo Chung, Jean-Jacques E. Slotine

Annu. Rev. Control., 2021

A Theoretical Overview of Neural Contraction Metrics for Learning-based Control with Guaranteed Stability.

Hiroyasu Tsukamoto, Soon-Jo Chung, Jean-Jacques E. Slotine, Chuchu Fan

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Learning-based Adaptive Control using Contraction Theory.

Hiroyasu Tsukamoto, Soon-Jo Chung, Jean-Jacques E. Slotine

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Safe Motion Planning with Tubes and Contraction Metrics.

Sumeet Singh, Hiroyasu Tsukamoto, Brett Thomas Lopez, Soon-Jo Chung, Jean-Jacques E. Slotine

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

Neural Stochastic Contraction Metrics for Learning-based Robust Control and Estimation.

Hiroyasu Tsukamoto, Soon-Jo Chung, Jean-Jacques E. Slotine

CoRR, 2020

2019

Convex Optimization-based Controller Design for Stochastic Nonlinear Systems using Contraction Analysis.

Hiroyasu Tsukamoto, Soon-Jo Chung

Proceedings of the 58th IEEE Conference on Decision and Control, 2019