Hiroyasu Tsukamoto, a PhD student at Caltech
My research interests include autonomous decision making and control of general nonlinear systems, machine learning-based optimal control, estimation, and motion planning of aerial swarms and autonomous aerospace systems. I am a recipient of the Caltech Vought Fellowship and the Funai Overseas Scholarship for graduate studies.
Education
- Ph.D. Candidate in Space Engineering (Jun. 2018 – Present), Caltech
- M. Sc. in Space Engineering (Jun. 2018), GPA: 4.2/4.0, Caltech
- B. Eng. in Aerospace Engineering (Mar. 2017), GPA: 3.8/4.0, Kyoto University
Past Projects
- Robust Controller Design for Stochastic Nonlinear Systems via Convex Optimization@Aerospace Robotics and Control Laboratory, Caltech (Apr. 2018 – Sep. 2019, Advisor: Prof. Soon-Jo Chung)
- Proposed a convex optimization-based robust feedback control framework for a class of Ito stochastic nonlinear systems
- Provably-Stable Reinforcement Learning in Continuous State and Action Spaces@Laboratory for Dynamics in Aeronautics and Astronautics, Kyoto University (Apr. 2016 – Jun. 2017, Advisor: Prof. Kei Senda)
- Proposed approximate RL in continuous state and action spaces with guaranteed convergence using neural networks
- Space Mission Design to Jupiter Galilean Moons@Research Institute for Sustainable Humanosphere (RISH), Kyoto University (Oct. 2015 – Mar. 2016, Advisor: Prof. Hiroshi Yamakawa)
- Designed optimal low-thrust trajectories to the Jupiter Galilean moons with multiple gravity-assists and gravitational-captures via SQP
- Analysis of HCN Emissivity as Interstellar Medium@Institute of Theoretical Astrophysics (ITA), University of Heidelberg (Feb. 2016, Advisors: Prof. Ralf S. Klessen and Dr. Simon C. O. Glover)
- Human Error Analysis in Space experiments at International Space Station (ISS)@Human Space Safety and Mission Assurance Office, Human Spaceflight Technology Directorate, JAXA (Sep. 2015)
