Journal Articles JSR Hierarchical Reinforcement Learning Framework for Stochastic Spaceflight Campaign Design Yuji Takubo, Hao Chen, and Koki Ho Journal of Spacecraft and Rockets 2022 Bib HTML @article{takubo2022hrl, title = {Hierarchical Reinforcement Learning Framework for Stochastic Spaceflight Campaign Design}, author = {Takubo, Yuji and Chen, Hao and Ho, Koki}, journal = {Journal of Spacecraft and Rockets}, volume = {59}, number = {2}, pages = {421--433}, year = {2022}, publisher = {American Institute of Aeronautics and Astronautics}, } JSR Multidisciplinary Design Optimization Approach to Integrated Space Mission Planning and Spacecraft Design Masafumi Isaji, Yuji Takubo, and Koki Ho Journal of Spacecraft and Rockets 2022 Bib HTML @article{isaji2022mdo, title = {Multidisciplinary Design Optimization Approach to Integrated Space Mission Planning and Spacecraft Design}, author = {Isaji, Masafumi and Takubo, Yuji and Ho, Koki}, journal = {Journal of Spacecraft and Rockets}, volume = {59}, number = {5}, pages = {1660--1670}, year = {2022}, publisher = {American Institute of Aeronautics and Astronautics}, } Automated Tour Design in the Saturnian System Yuji Takubo, Damon Landau, and Brian Anderson In 33rd AAS/AAIA Space Flight Mechanics Meeting 2023, Austin, TX (Full paper Accepted.arXiv preprint arXiv:2210.14996) 2023 Bib HTML @inproceedings{takubo2023automated, title = {Automated Tour Design in the Saturnian System}, author = {Takubo, Yuji and Landau, Damon and Anderson, Brian}, booktitle = {33rd AAS/AAIA Space Flight Mechanics Meeting 2023, Austin, TX (Full paper Accepted.arXiv preprint arXiv:2210.14996)}, year = {2023}, } CEC Robust Constrained Multi-objective Evolutionary Algorithm based on Polynomial Chaos Expansion for Trajectory Optimization Yuji Takubo, and Masahiro Kanazaki In 2022 IEEE Congress on Evolutionary Computation (CEC) 2022 Bib HTML @inproceedings{takubo2022robsut, author = {Takubo, Yuji and Kanazaki, Masahiro}, booktitle = {2022 IEEE Congress on Evolutionary Computation (CEC)}, title = {Robust Constrained Multi-objective Evolutionary Algorithm based on Polynomial Chaos Expansion for Trajectory Optimization}, year = {2022}, volume = {}, number = {}, pages = {1-9}, doi = {10.1109/CEC55065.2022.9870365}, } Multidisciplinary Design Optimization Approach to Integrated Space Mission Planning and Spacecraft Design Masafumi Isaji, Yuji Takubo, and Koki Ho In ASCEND 2021 2021 Bib HTML @inproceedings{isaji2021mdo, title = {Multidisciplinary Design Optimization Approach to Integrated Space Mission Planning and Spacecraft Design}, url = {https://par.nsf.gov/biblio/10319105}, doi = {10.2514/6.2021-4069}, booktitle = {ASCEND 2021}, author = {Isaji, Masafumi and Takubo, Yuji and Ho, Koki}, year = {2021}, } Robust Multi‑objective Optimization of the Control Input of Trajectory Planning (「経路設計のための制御入力の多目的ロバスト最適化」) Yuji Takubo, and Masahiro Kanazaki In The 20th Japanese Society of Evolutionary Computation Symposium (第20回日本進化計算学会研究会) 2021 Bib PDF @inproceedings{takubo2021robust, author = {Takubo, Yuji and Kanazaki, Masahiro}, booktitle = {The 20th Japanese Society of Evolutionary Computation Symposium (第20回日本進化計算学会研究会)}, title = {Robust Multi‑objective Optimization of the Control Input of Trajectory Planning (「経路設計のための制御入力の多目的ロバスト最適化」)}, year = {2021}, volume = {}, number = {}, } Performance Analysis of Hierarchical Reinforcement Learning Framework for Stochastic Space Logistics Yuji Takubo, Hao Chen, and Koki Ho In ASCEND 2020 2020 Bib HTML @inproceedings{takubo2020perf_hrl, title = {Performance Analysis of Hierarchical Reinforcement Learning Framework for Stochastic Space Logistics}, author = {Takubo, Yuji and Chen, Hao and Ho, Koki}, booktitle = {ASCEND 2020}, pages = {4230}, year = {2020}, } Conference Papers Automated Tour Design in the Saturnian System Yuji Takubo, Damon Landau, and Brian Anderson In 33rd AAS/AAIA Space Flight Mechanics Meeting 2023, Austin, TX (Full paper Accepted.arXiv preprint arXiv:2210.14996) 2023 Bib HTML @inproceedings{takubo2023automated, title = {Automated Tour Design in the Saturnian System}, author = {Takubo, Yuji and Landau, Damon and Anderson, Brian}, booktitle = {33rd AAS/AAIA Space Flight Mechanics Meeting 2023, Austin, TX (Full paper Accepted.arXiv preprint arXiv:2210.14996)}, year = {2023}, } CEC Robust Constrained Multi-objective Evolutionary Algorithm based on Polynomial Chaos Expansion for Trajectory Optimization Yuji Takubo, and Masahiro Kanazaki In 2022 IEEE Congress on Evolutionary Computation (CEC) 2022 Bib HTML @inproceedings{takubo2022robsut, author = {Takubo, Yuji and Kanazaki, Masahiro}, booktitle = {2022 IEEE Congress on Evolutionary Computation (CEC)}, title = {Robust Constrained Multi-objective Evolutionary Algorithm based on Polynomial Chaos Expansion for Trajectory Optimization}, year = {2022}, volume = {}, number = {}, pages = {1-9}, doi = {10.1109/CEC55065.2022.9870365}, } Multidisciplinary Design Optimization Approach to Integrated Space Mission Planning and Spacecraft Design Masafumi Isaji, Yuji Takubo, and Koki Ho In ASCEND 2021 2021 Bib HTML @inproceedings{isaji2021mdo, title = {Multidisciplinary Design Optimization Approach to Integrated Space Mission Planning and Spacecraft Design}, url = {https://par.nsf.gov/biblio/10319105}, doi = {10.2514/6.2021-4069}, booktitle = {ASCEND 2021}, author = {Isaji, Masafumi and Takubo, Yuji and Ho, Koki}, year = {2021}, } Robust Multi‑objective Optimization of the Control Input of Trajectory Planning (「経路設計のための制御入力の多目的ロバスト最適化」) Yuji Takubo, and Masahiro Kanazaki In The 20th Japanese Society of Evolutionary Computation Symposium (第20回日本進化計算学会研究会) 2021 Bib PDF @inproceedings{takubo2021robust, author = {Takubo, Yuji and Kanazaki, Masahiro}, booktitle = {The 20th Japanese Society of Evolutionary Computation Symposium (第20回日本進化計算学会研究会)}, title = {Robust Multi‑objective Optimization of the Control Input of Trajectory Planning (「経路設計のための制御入力の多目的ロバスト最適化」)}, year = {2021}, volume = {}, number = {}, } Performance Analysis of Hierarchical Reinforcement Learning Framework for Stochastic Space Logistics Yuji Takubo, Hao Chen, and Koki Ho In ASCEND 2020 2020 Bib HTML @inproceedings{takubo2020perf_hrl, title = {Performance Analysis of Hierarchical Reinforcement Learning Framework for Stochastic Space Logistics}, author = {Takubo, Yuji and Chen, Hao and Ho, Koki}, booktitle = {ASCEND 2020}, pages = {4230}, year = {2020}, }