Journal

1. Yunduan Cui, Lei Peng, and Huiyun Li. “Filtered Probabilistic Model Predictive Control-based Reinforcement Learning for Unmanned Surface Vehicles.” IEEE Transactions on Industrial Informatics, 2022. link

2. Dezhou Xu, Yunduan Cui, Jiaye Ye, Suk Won Cha, Aimin Li, and Chunhua Zheng. “A soft actor-critic-based energy management strategy for electric vehicles with hybrid energy storage systems.” Journal of Power Sources, 2022. link

3. Yujun Lai, Gavin Paul, Yunduan Cui, and Takamitsu Matsubara. “User intent estimation during robot learning using physical human robot interaction primitives.” Autonomous Robots, 2022. link

4. Wei Li, Jiaye Ye, Yunduan Cui, Namwook Kim, Suk Won Cha, and Chunhua Zheng. “A Speedy Reinforcement Learning-Based Energy Management Strategy for Fuel Cell Hybrid Vehicles Considering Fuel Cell System Lifetime.” International Journal of Precision Engineering and Manufacturing-Green Technology, 2021. link

5. Cheng-Yu Kuo, Andreas Schaarschmidt, Yunduan Cui, Tamim Asfour, and Takamitsu Matsubara. “Uncertainty-aware Contact-safe Model-based Reinforcement Learning.” IEEE Robotics and Automation Letters (with ICRA 2021), 2021. link

6. Yunduan Cui, Osaki Shigeki, and Takamitsu Matsubara. “Autonomous Boat Driving System using Sample-efficient Model Predictive Control-based Reinforcement Learning Approach.” Journal of Field Robotics, 2020. link

7. Yunduan Cui, Junichiro Ooga, Akihito Ogawa, and Takamitsu Matsubara. “Probabilistic Active Filtering with Gaussian Processes for Occluded Object Search in Clutter.” Applied Intelligence, 2020. link

8. Lingwei Zhu, Yunduan Cui, Go Takami, Hiroaki Kanokogi, and Takamitsu Matsubara. “Scalable Reinforcement Learning for Plant-wide Control of Vinyl Acetate Monomer Process.” Control Engineering Practice, 2020. link

9. Yoshihisa Tsurumine, Yunduan Cui, Eiji Uchibe, and Takamitsu Matsubara. “Deep reinforcement learning with smooth policy update: Application to robotic cloth manipulation.” Robotics and Autonomous Systems, 2018. link

10. Yunduan Cui, James Poon, Jaime Valls Miro, Kimitoshi Yamazaki, Kenji Sugimoto, and Takamitsu Matsubara. “Environment-adaptive interaction primitives through visual context for human–robot motor skill learning.” Autonomous Robots, 2018. link

11. Yunduan Cui, Takamitsu Matsubara, and Kenji Sugimoto. “Kernel dynamic policy programming: Applicable reinforcement learning to robot systems with high dimensional states.” Neural Networks, 2017. (2018 Japanese Neural Network Society Best Paper Award) link

12. Yunduan Cui, Takamitsu Matsubara, and Kenji Sugimoto. “Pneumatic artificial muscle-driven robot control using local update reinforcement learning.” Advanced Robotics, 2017. link

International Conference

1. Zhiwei Shang, Huiyun Li, and Yunduan Cui. “Shiftable Dynamic Policy Programming for Efficient and Robust Reinforcement Learning Control.” IEEE International Conference on Robotics and Biomimetics (ROBIO) 2021.

2. Naitian Deng, Yunduan Cui, Shitian Zhang, and Huiyun Li. “Autonomous Vehicle Motion Planning using Kernelized Movement Primitives.” International Symposium on Networks, Computers and Communications (ISNCC) 2021. link

3. Shitian Zhang, Yunduan Cui, Naitian Deng, and Huiyun Li. “Model Predictive Control of Autonomous Driving using Unscented Kalman Filter with Sparse Spectrum Gaussian Processes.” International Symposium on Networks, Computers and Communications (ISNCC) 2021. link

4. Lingwei Zhu, Yunduan Cui, and Takamitsu Matsubara. “Dynamic Actor-Advisor Programming for Scalable Safe Reinforcement Learning.” IEEE International Conference on Robotics and Automation (ICRA) 2020. link

5. Cheng-Yu Kuo, Yunduan Cui, and Takamitsu Matsubara. “Sample-and-computational-efficient Probabilistic Model Predictive Control with Random Features.” IEEE International Conference on Robotics and Automation (ICRA) 2020. link

6. Yunduan Cui, Shigeki Osaki, Takamitsu Matsubara. “Reinforcement Learning Ship Autopilot: Sample-efficient and Model Predictive Control-based Approach.” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2019. ArXiv preprint arXiv:1901.07905 SICE International Young Authors Award 2019 (IROS) link

7. Yoshihisa Tsurumine, Yunduan Cui, Kimitoshi Yamazaki, Takamitsu Matsubara. “Generative Adversarial Imitation Learning with Deep P-Network for Robotic Cloth Manipulation” IEEE-RAS International Conference on Humanoid Robots (Humanoids) 2019. link

8. James Poon, Yunduan Cui, Junichiro Ohga, Akihito Ogawa, and Takamitsu Matsubara. “Probabilistic Active Filtering for Object Search in Clutter.” IEEE International Conference on Robotics and Automation (ICRA) 2019. link

9. James Poon, Yunduan Cui, Jaime Valls Miro, Takamitsu Matsubara. “Learning Mobility Aid Assistance via Decoupled Observation Models.” International Conference on Control, Automation, Robotics and Vision (ICARCV 2018). link

10. Yunduan Cui, Lingwei Zhu, Morihiro Fujisaki, Hiroaki Kanokogi, and Takamitsu Matsubara. “Factorial Kernel Dynamic Policy Programming for Vinyl Acetate Monomer Plant Model Control.” IEEE International Conference on Automation Science and Engineering (CASE) 2018. link

11. Takamitsu Matsubara, Yu Norinaga, Yuto Ozawa, and Yunduan Cui. “Policy Transfer from Simulations to Real World by Transfer Component Analysis.” IEEE International Conference on Automation Science and Engineering (CASE) 2018. link

12. Yoshihisa Tsurumine, Yunduan Cui, Eiji Uchibe, and Takamitsu Matsubara. “Deep Dynamic Policy Programming for Robot Control with Raw Images.” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2017. link

13. James Poon, Yunduan Cui, Jaime Valls Miro, Takamitsu Matsubara, and Kenji Sugimoto. “Local Driving Assistance from Demonstration for Mobility Aids.” IEEE International Conference on Robotics and Automation (ICRA) 2017. link

14. Yunduan Cui, James Poon, Takamitsu Matsubara, Jaime Valls Miro, Kenji Sugimoto, and Kimitoshi Yamazaki. “Environment-adaptive Interaction Primitives for Human-Robot Motor Skill Learning.” IEEE-RAS International Conference on Humanoid Robots (Humanoids) 2016. link

15. Yunduan Cui, Takamitsu Matsubara, and Kenji Sugimoto. “Kernel Dynamic Policy Programming: Practical Reinforcement Learning for High-dimensional Robots.” IEEE-RAS International Conference on Humanoid Robots (Humanoids) 2016. ( Best Oral Paper Award) link

16. Yunduan Cui, Takamitsu Matsubara, and Kenji Sugimoto. “Local Update Dynamic Policy Programming in reinforcement learning of pneumatic artificial muscle-driven humanoid hand control.” IEEE-RAS International Conference on Humanoid Robots (Humanoids) 2015. link

17. Yunduan Cui, Kazuhiko Takahashi, and Masafumi Hashimoto. “Remarks on quaternion neural network based controller with application to an inverted pendulum.” 2014 SICE Annual Conference. link

18. Kazuhiko Takahashi, Sae Takahashi, Yunduan Cui and Masafumi Hashimoto. “Remarks on computational facial expression recognition from HOG features using quaternion multi-layer neural network.” 2014 International Conference on Engineering Applications of Neural Networks. link

19. Yunduan Cui, Kazuhiko Takahashi, and Masafumi Hashimoto. “Remarks on robot controller application of Clifford multi-layer neural networks.” 2014 IEEE 13th International Workshop on Advanced Motion Control (AMC). link

20. Yunduan Cui, Kazuhiko Takahashi, and Masafumi Hashimoto. “Design of control systems using quaternion neural network and its application to inverse kinematics of robot manipulator.” 2013 IEEE/SICE International Symposium on System Integration (SII). link