Publications
Please also refer to my Google Scholar and ResearchGate.
Journal Articles
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Takubo, Y., Landau, D., and Brian, A. “Automated Tour Design in the Saturnian System,” Celestial Mechanics and Dynamical Astronomy, Vol. 136, article 8, 2024.
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Takubo, Y., and Kanazaki, M., “Robust Constrained Multi-objective Optimal Guidance of Supersonic Transport Landing based on Evolutionary Algorithm and Polynomial Chaos,” MDPI Aerospace, 10(11), pp.929, 2023.
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Woodall, B., Borowitz, M., Watkins, K., Costa, M., Howard, A., Kemerait, P., Lee, M., Rolls, G., Takubo, Y., Titshaw, R. and Winstead, M., “The megaregion–forms, functions, and potential? A literature review and proposal for advancing research,” International Journal of Urban Sciences, 2023.
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Isaji, M., Takubo, Y., and Ho, K., “Multidisciplinary Design Optimization Approach to Integrated Space Mission Planning and Spacecraft Design,” Journal of Spacecraft and Rockets, 59(5), pp. 1660-1670, 2022.
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Takubo, Y., Chen, H., and Ho, K., “Hierarchical Reinforcement Learning Framework for Stochastic Spaceflight Campaign Design,” Journal of Spacecraft and Rockets, 59(2), pp.421‑433, 2022.
Conference Papers
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Takubo, Y., Shimane, Y., and Ho, K., ``Optimization of Earth-Moon Low-Thrust-Enhanced Low-Energy Transfer,’’ 2023 AAS/AIAA Aerodynamics Specialist Conference, Big Sky, MT, Aug. 2023. (PDF)
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Takubo, Y., Landau, D., and Brian, A. “Automated Tour Design in the Saturnian System,” 33rd AAS/AIAA Space Flight Mechanics Meeting, Austin, TX, 2023 (Breakwell Student Paper Award, available on arXiv).
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Takubo, Y., and Kanazaki, M., “Robust Constrained Multi‑objective Evolutionary Algorithm based on Polynomial Chaos Expansion for Trajectory Optimization,” IEEE Congress on Evolutionary Computation, IEEE WCCI 2022, Padua, Italy, Jul. 2022
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Takubo, Y., and Kanazaki, M., “Robust Multi‑objective Optimization of the Control Input of Trajectory Planning,” The 20th Symposium of the Japanese Society for Evolutionary Computation, Online, Sep. 2021. (Japanese: “経路設計のための制御入力の多目的ロバスト最適化,” 第20回日本進化計算学会研究会) 2022 Best Paper Award.
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Isaji, M., Takubo, Y., and Ho, K., “Multidisciplinary Design Optimization Approach to Integrated Space Mission Planning and Spacecraft Design,” AIAA ASCEND, Las Vegas, NV, Oct. 2021.
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Takubo, Y., Chen, H., and Ho, K., “Performance Analysis of Hierarchical Reinforcement Learning Framework for Stochastic Space Logistics,” AIAA ASCEND, Online, Oct. 2020.