Journal

1. Jia Liu, Yunduan Cui, Jianghua Duan, Zhengmin Jiang, Zhongming Pan, Kun Xu, and Huiyun Li, “Reinforcement Learning-Based High-Speed Path Following Control for Autonomous Vehicles.” IEEE Transactions on Vehicular Technology, 2024. link (IF 6.8, JCR Q1)

2. Dongfang Zhang, Yunduan Cui, Yao Xiao, Shengxiang Fu, Suk Won Cha, Namwook Kim, Hongyan Mao, and Chunhua Zheng. “An Improved Soft Actor-Critic-Based Energy Management Strategy of Fuel Cell Hybrid Vehicles with a Nonlinear Fuel Cell Degradation Model.” International Journal of Precision Engineering and Manufacturing-Green Technology, 2024. link (IF 4.2, JCR Q1)

3. Zhiwei Shang, Renxing Li, Chunhua Zheng, Huiyun Li, and Yunduan Cui. “Relative Entropy Regularized Sample-Efficient Reinforcement Learning With Continuous Actions.” IEEE Transactions on Neural Networks and Learning Systems, 2023. link (IF 10.4, JCR Q1)

4. Yixuan Ku, Chen Guo, Kangshuai Zhang, Yunduan Cui, Hongfeng Shu, Yang Yang, Lei Peng. “Toward Directed Spatiotemporal Graph: A New Idea for Heterogeneous Traffic Prediction.” IEEE Intelligent Transportation Systems Magazine, 2023. link (IF 3.6, JCR Q1)

5. Yunduan Cui, Kun Xu, Chunhua Zheng, Jia Liu, Lei Peng, and Huiyun Li. “Flexible Unmanned Surface Vehicles Control using Probabilistic Model-based Reinforcement Learning with Hierarchical Gaussian Distribution.” Ocean Engineering, 2023. link (IF 5.0, JCR Q1)

6. Renxing Li, Zhiwei Shang, Chunhua Zheng, Huiyun Li, Qing Liang, and Yunduan Cui. “Efficient Distributional Reinforcement Learning with Kullback-Leibler Divergence Regularization.” Applied Intelligence, 2023. link (IF 5.3, JCR Q2)

7. Yunduan Cui, Wenbo Shi, Huan Yang, Cuiping Shao, Lei Peng, and Huiyun Li. “Probabilistic Model-Based Reinforcement Learning Unmanned Surface Vehicles Using Local Update Sparse Spectrum Approximation.” IEEE Transactions on Industrial Informatics, 2023. link (IF 12.3, JCR Q1)

8. Jincheng Wang, Lei Xia, Lei Peng, Huiyun Li, and Yunduan Cui. “Efficient Uncertainty Propagation in Model-Based Reinforcement Learning Unmanned Surface Vehicle Using Unscented Kalman Filter.” Drones, 2023. link (IF 4.8, JCR Q2)

9. Dezhou Xu, Chunhua Zheng, Yunduan Cui, Shengxiang Fu, Namwook Kim, and Suk Won Cha. “Recent progress in learning algorithms applied in energy management of hybrid vehicles: a comprehensive review.” International Journal of Precision Engineering and Manufacturing-Green Technology, 2023. link (IF 4.2, JCR Q1)

10. Cuiping Shao, Beizhang Chen, Zujia Miao, Yunduan Cui, Huiyun Li. “Anomaly recognition method of perception system for autonomous vehicles based on distance metric.” Electronics Letters, 2022. link (IF 1.1, JCR Q4)

11. 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 (IF 12.3, JCR Q1)

12. 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 (IF 9.2, JCR Q1)

13. 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 (IF 3.5, JCR Q2)

14. 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 (IF 4.2, JCR Q1)

15. 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 (IF 5.2, JCR Q2)

16. 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, 2021. link (IF 8.3, JCR Q1)

17. 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 (IF 5.3, JCR Q2)

18. 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 (IF 4.9, JCR Q2)

19. 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

20. 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 (IF 4.3, JCR Q2)

21. 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 (IF 7.8, JCR Q1)

22. Yunduan Cui, Takamitsu Matsubara, and Kenji Sugimoto. “Pneumatic artificial muscle-driven robot control using local update reinforcement learning.” Advanced Robotics, 2017. link (IF 2.0, JCR Q4)

International Conference

1. Lei Xia, Cuiping Shao, Huiyun Li, and Yunduan Cui. “Robust Model-based Reinforcement Learning USV System Guided by Lyapunov Neural Networks.” IEEE International Conference on Robotics and Biomimetics (ROBIO) 2022. link

2. Cuiping Shao, Zujia Miao, Beizhang Chen, Yunduan Cui, Huiyun Li, and Hongfeng Shu, “An Attack Detection Method Based on Spatiotemporal Correlation for Autonomous Vehicles Sensors.” IEEE International Conference on Intelligent Transportation Systems (ITSC) 2022. link

3. Yunfu Deng, Kun Xu, Yue Hu, Yunduan Cui, Gengzhao Xiang, and Zhongming Pan, “Learning Effectively from Intervention for Visual-based Autonomous Driving.” IEEE International Conference on Intelligent Transportation Systems (ITSC) 2022. link

4. Deliang Liu, Kun Xu, Yunduan Cui, Yujie Zou, and Zhongming Pan, “Learning-based Motion Control of Autonomous Vehicles Considering Varying Adhesion Road Surfaces.” IEEE International Conference on Intelligent Transportation Systems (ITSC) 2022. link

5. Jincheng Wang, Kun Xu, Cuiping Shao, Lei Peng, and Yunduan Cui, “Data-Driven Probabilistic Model of Magneto-Rheological Damper for Intelligent Vehicles using Gaussian Processes.” IEEE International Conference on Intelligent Transportation Systems (ITSC) 2022. link

6. Renxing Li, Zhiwei Shang, Chunhua Zheng, Huiyun Li, Qing Liang, and Yunduan Cui, “Dynamic Policy Programming with Descending Regularization for Efficient Reinforcement Learning Control.” International Conference on Pattern Recognition and Artificial Intelligence (PRAI) 2022. link

7. 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. link

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

14. 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

15. 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

16. 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

17. 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

18. 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

19. 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

20. 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

21. 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

22. 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

23. 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

24. 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

25. 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

26. 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