I am an Associate Professor at the College of Intelligence Science and Technology, National University of Defense Technology (NUDT), Changsha, China.

My research interests include learning-based predictive control, safe reinforcement learning, and their applications in robotics, with a special focus on autonomous vehicles.

Recent News

• I serve as a co-chair for the invited session “Multi-Platform Autonomous Cooperative Perception, Cognition and Decision-Making in Confrontational Environment ” with submission code P2VNPK at the 2024 7th IEEE International Conference on Unmanned Systems.
• I serve as a PC member at the 7th Asian Conference on Artificial Intelligence Technology.
• June 24, 2024, Our paper “Game-theoretic Receding-Horizon Reinforcement Learning for Lateral Control of Autonomous Vehicles” published at IEEE Transactions on Vehicular Technology!
• February, 2024, Our paper “Learning-Based Near-Optimal Motion Planning for Intelligent Vehicles With Uncertain Dynamics” published at IEEE Robotics and Automation Letters!
• January 4, 2024, Our paper “Model-Based Safe Reinforcement Learning With Time-Varying Constraints: Applications to Intelligent Vehicles” published at IEEE Transactions on Industrial Electronics!
• August 12, 2023, Our paper “Self-learning Sliding Mode Control Based on Adaptive Dynamic Programming for Nonholonomic Mobile Robots” published at ISA Transactions!
• January 29, 2023, Our paper “Receding Horizon Actor-Critic Learning Control for Nonlinear Time-Delay Systems with Unknown Dynamics” accepted at IEEE Transactions on Systems, Man, and Cybernetics: Systems!
• January 11, 2023, Our paper “A Deep Koopman Approach for Longitudinal and Lateral Control of Autonomous Ground Vehicles” accepted at ICRA 2023!
• November 14, 2022, Our paper “Robust consensus control of nonlinear multi-agent systems based on convergence rate estimation” published at International Journal of Robust and Nonlinear Control!
• September 2, 2022, Our paper “A Dual-level Model Predictive Control Scheme for Multi-timescale Dynamical Systems” accepted to IEEE Transactions on Systems, Man, and Cybernetics: Systems!
• July, 2022, Our paper “Data-driven Kalman Filter with Kernel-based Koopman Operators for Nonlinear Robot Systems” accepted to IROS 2022!
• I serve as a Guest Editor on a special issue at the Journal: “Applied Sciences” (IF=2.7).
• May, 2022, Our paper “Deep Neural Networks with Koopman Operators for Modeling and Control of Autonomous Vehicles” accepted to IEEE Transactiosn on Intelligent Vehicles 2022!
• I serve as a PC member at the 6th Asian Conference on Artificial Intelligence Technology.
• March 30, 2022, Our paper “A Receding-Horizon Reinforcement Learning Approach for Kinodynamic Motion Planning of Autonomous Vehicles” accepted to IEEE Transactiosn on Intelligent Vehicles 2022!
• February 1, 2022, Our paper “Barrier Function-based Safe Reinforcement Learning for Formation Control of Mobile Robots” accepted to ICRA 2022!
• January 12, 2022, Our paper “Robust Learning-based Predictive Control for Discrete-time Nonlinear Systems with Unknown Dynamics and State Constraints” accepted to IEEE Transactions on Systems, Man, and Cybernetics: Systems!
• December 19, 2021, Our preprint “Model-Based Safe Reinforcement Learning with Time-Varying State and Control Constraints: An Application to Intelligent Vehicles” uploaded at TechRxiv and arXiv!
• I will server as a session chair on the topic “AI, Intelligent Control for Autonomous Robots” at IEEE ARM 2022, the submission code of our session is 4999h!!!
• November 30, 2021, Our paper “Continuous‐time receding‐horizon reinforcement learning and its application to path‐tracking control of autonomous ground vehicles” published at Optimal Control Applications and Methods!
• November 2, 2021, Our paper “基于滚动时域强化学习的智能车辆侧向控制算法 (doi:10.16383/j.aas.c210555)” accepted to 自动化学报 (Acta Automatica Sinica)!
• October 25, 2021, Our paper “Robust Tube-based Model Predictive Control with Koopman Operators” accepted to Automatica!
• September 29, 2021, Our paper “Dual heuristic programming with just‐in‐time modeling for self‐learning fault‐tolerant control of mobile robots” published at Optimal Control Applications and Methods!