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I am a PhD student in the JSK Lab at the University of Tokyo. My research focuses on developing learning methods for robotic skills (motion planning and manipulation) which explicitly take advantage of feasibility and capability assessment. Research range includes data-driven motion planning (T-RO 2025) and policy search for manipulation (RA-L 2021).

Alongside research activities, I like writing fast and well modularized software. A notable work includes plainmp: a highly tuned motion planning library for articulated robots written in C++ with Python bindings. It solves moderately complex planning problems (e.g., 8DOF Fetch in front of table) in less than 1ms on a laptop, which is, to my knowledge, significantly faster compared to standard implementations.

My industrial experience includes SB Intuitions (2025.7~) full-time, where I will be contributing to launching their robotics team as the very first member. I experienced part-time jobs at two companies: Tier IV (2021.4 - 2022.6), where I worked on autonomous driving software and gained experience developing high-quality software in a team with large codebases (Some PRs are publicly available here). At Integral AI (2024.4 - 2024.11), a startup company, I gained valuable experience working on projects in the very initial phases.

Contact

Education

  • 2019.4 - Present: Ph.D. student in Mechano-Informatics, The University of Tokyo
  • 2016.4 - 2018.3: M.Eng. in Aerospace Engineering, The University of Tokyo
  • 2012.4 - 2016.3: M.Eng. in Aerospace Engineering, Osaka Prefecture University

Fellowships and scholarships

  • JSPS Postdoctoral Research Fellow (学振特別研究員PD), 2024 (withdrawn due to postponement of graduation)
  • Scholarship for study abroad by Nakajima Foundation (中島記念国際交流財団海外留学奨学金), Nov. 2017. (withdrawn)

Selected publications

  • H. Ishida, N. Hiraoka, K. Okada and M. Inaba CoverLib: Classifiers-equipped Experience Library by Iterative Problem Distribution Coverage Maximization for Domain-tuned Motion Planning, IEEE Transactions on Robotics (T-RO), 2025, arXiv link, IEEE link.

  • N. Hiraoka, H. Ishida, T. Hiraoka, K. Kojima, K. Okada, M. Inaba: Sampling-based Global Path Planning using Convex Polytope Approximation for Narrow Collision-free Space of Humanoid. International Journal of Humanoid Robotics, 2024, Paper link.

  • H. Ishida, K. Okada and M. Inaba, Classifier-Aided Maximization of Feasible-Error-Region for Robust Manipulation Learning, IEEE Robotics and Automation Letters (RA-L), 2021, Paper link.

  • T. Chujo, H. Ishida, O. Mori, J. Kawaguchi: Liquid crystal device with reflective microstructure for attitude control, Journal of Spacecraft and Rockets, 2018, Paper link.

  • H. Ishida, T. Chujo, O. Mori, J. Kawaguchi: Optimal design of advanced reflectivity control device for solar sails considering polarization properties of liquid crystal, Proceedings of the 26th International Symposium on Space Flight Dynamics (ISSFD), 2017, Paper link.

Other publications

  • L. Wu, H. Jia, K. Kawaharazuka, H. Ishida, K. Okada, Dexterous Grasp Data Augmentation based on Grasp Synthesis with Fingertip Workspace Cloud and Contact-Aware Sampling, Advanced Robotics, 2025 (in press).

  • J. Kawaguchi, O. Mori, T. Chujo, H. Ishida: Optical device, attitude control apparatus, and spacecraft. United States patent US 11,679,901. 2023 Jun 20, link.

  • H. Ishida, Y. Tsuda, Robust terrain-aided localization of spacecraft using low-fidelity asteroid shape model, SICE International Symposium on Control System, 2018, Paper link.

  • H. Ishida, T. Chujo, O. Mori, J. Kawaguchi: Evaluation of Optical Properties of Advanced Reflectivity Control Device for Solar Sails by Numerical Simulation, 68th International Astronautical Congress (IAC), 2017, Paper link.

  • H. Ishida, Y. Tsuda: Range Measurement based Localization between Mothership and Lander Considering Asteroid Shape Using Particle Filter, Proceedings of the 26th International Symposium on Space Flight Dynamics (ISSFD), 2017.