Publications
(2023). Model-Free Safe Reinforcement Learning through Neural Barrier Certificate. In IEEE Robotics and Automation Letters (RAL), 2023.

(2023). Chance-Constrained Iterative Linear-Quadratic Stochastic Games. In IEEE Robotics and Automation Letters (RAL), 2023.

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(2022). Policy-Iteration-Based Finite-Horizon Approximate Dynamic Programming for Continuous-Time Nonlinear Optimal Control. In IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.

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(2022). Reinforcement learning with Demonstrations from Mismatched Task under Sparse Reward. In Conference on Robot Learning (CoRL), 2022.

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(2022). Unsupervised Skill Discovery via Recurrent Skill Training. In Conference on Neural Information Processing Systems (NeurIPS), 2022.

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(2022). Decomposed Mutual Information Optimization for Generalized Context in Meta-Reinforcement Learning. In Conference on Neural Information Processing Systems (NeurIPS), 2022.

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(2022). An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context. In Conference on Neural Information Processing Systems (NeurIPS), 2022.

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(2022). A Contact-Safe Reinforcement Learning Framework for Contact-Rich Robot Manipulation. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022.

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(2022). Flow-based Recurrent Belief State Learning for POMDPs. In International Conference on Machine Learning (ICML), 2022.

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(2022). Reachability Constrained Reinforcement Learning. In International Conference on Machine Learning (ICML), 2022.

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(2022). CtrlFormer: Learning Transferable State Representation for Visual Control via Transformer. In International Conference on Machine Learning (ICML), 2022.

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(2022). Performance-Driven Controller Tuning via Derivative-Free Reinforcement Learning. In IEEE Conference on Decision and Control (CDC), 2022.

(2022). Joint Synthesis of Safety Certificate and Safe Control Policy using Constrained Reinforcement Learning. In Annual Conference on Learning for Dynamics and Control (L4DC), 2022 (Best Paper Award Finalists).

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(2022). Learning POMDP Models with Similarity Space Regularization: a Linear Gaussian Case Study. In Annual Conference on Learning for Dynamics and Control (L4DC), 2022.

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(2022). Learn to Grasp with Less Supervision: A Data-Efficient Maximum Likelihood Grasp Sampling Loss. In IEEE International Conference on Robotics and Automation (ICRA), 2022.

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(2022). Model-Based Chance-Constrained Reinforcement Learning via Separated Proportional-Integral Lagrangian. In IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.

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(2022). Scale-Equivalent Distillation for Semi-Supervised Object Detection. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.

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(2021). Model-based Actor-Critic with Chance Constraint for Stochastic System. In IEEE Conference on Decision and Control (CDC), 2021.

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(2021). Model-Based Reinforcement Learning via Imagination with Derived Memory. In Conference on Neural Information Processing Systems (NeurIPS), 2021.

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(2021). Belief State Separated Reinforcement Learning for Autonomous Vehicle Decision Making under Uncertainty. In IEEE International Intelligent Transportation Systems Conference (ITSC), 2021.

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(2021). Model-based Constrained Reinforcement Learning using Generalized Control Barrier Function. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021.

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(2021). Constrained Iterative LQG for Real-Time Chance-Constrained Gaussian Belief Space Planning. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021.

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(2021). Separated Proportional-Integral Lagrangian for Chance Constrained Reinforcement Learning. In IEEE Intelligent Vehicles Symposium (IV), 2021 (Best Student Paper Award Finalists).

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(2021). A Safe Hierarchical Planning Framework for Complex Driving Scenarios based on Reinforcement Learning. In IEEE International Conference on Robotics and Automation (ICRA), 2021.

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(2021). Enable Faster and Smoother Spatio-Temporal Trajectory Planning for Autonomous Vehicles in Constrained Dynamic Environment. In Proceedings of the Institution of Mechanical Engineers, Part D:Journal of Automobile Engineering, 2021.

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(2021). Interpretable End-to-End Urban Autonomous Driving with Latent Deep Reinforcement Learning. In IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2021.

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(2021). Reinforced Optimal Estimator. In Modeling, Estimation and Control Conference (MECC), 2021 (Best Student Paper Award Finalists).

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(2020). Motion Planning for Autonomous Driving With Extended Constrained Iterative LQR. In Dynamic Systems and Control Conference (DSCC), 2020.

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(2020). End-to-End Autonomous Driving Perception with Sequential Latent Representation Learning. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020.

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(2019). Deep Imitation Learning for Autonomous Driving in Generic Urban Scenarios with Enhanced Safety. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019.

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(2019). Model-Free Deep Reinforcement Learning for Urban Autonomous Driving. In IEEE Intelligent Transportation Systems Conference (ITSC), 2019.

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(2019). Adaptive Probabilistic Vehicle Trajectory Prediction Through Physically Feasible Bayesian Recurrent Neural Network. In IEEE International Conference on Robotics and Automation (ICRA), 2019.

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(2019). Autonomous Driving Motion Planning With Constrained Iterative LQR. In IEEE Transactions on Intelligent Vehicles (T-IV), 2019.

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(2018). Intention-aware Long Horizon Trajectory Prediction of Surrounding Vehicles using Dual LSTM Networks. In IEEE Intelligent Transportation Systems Conference (ITSC), 2018.

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(2018). FOAD: Fast Optimization-based Autonomous Driving Motion Planner. In Annual American Control Conference (ACC), 2018.

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(2018). Deep Hierarchical Reinforcement Learning for Autonomous Driving with Distinct Behaviors. In IEEE Intelligent Vehicles Symposium (IV), 2018.

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(2018). Continuous Decision Making for On-Road Autonomous Driving under Uncertain and Interactive Environments. In IEEE Intelligent Vehicles Symposium (IV), 2018 (Oral Presentation).

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(2018). Iterative Cross Learning on Noisy Labels. In IEEE Winter Conference on Applications of Computer Vision (WACV), 2018.

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(2017). Constrained Iterative LQR for On-Road Autonomous Driving Motion Planning. In IEEE Intelligent Transportation Systems Conference (ITSC), 2017.

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(2017). Spatially-Partitioned Environmental Representation and Planning Architecture for On-Road Autonomous Driving. In IEEE Intelligent Vehicles Symposium (IV), 2017.

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(2017). The Robustly-Safe Automated Driving System for Enhanced Active Safety. In SAE Technical Paper, 2017.

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