187 citations · 464 across the 21 of their papers we have counts for
6 papers · 1 filter
Model-Based Safe Reinforcement Learning with Time-Varying State and Control Constraints: An Application to Intelligent Vehicles
Xinglong Zhang, Yaoqian Peng, Biao Luo +3
Recently, safe reinforcement learning (RL) with the actor-critic structure for continuous control tasks has received increasing attention. It is still challenging to learn a near-o…
Robust Tube-based Model Predictive Control with Koopman Operators--Extended Version
Xinglong Zhang, Wei Pan, Riccardo Scattolini +2
Koopman operators are of infinite dimension and capture the characteristics of nonlinear dynamics in a lifted global linear manner. The finite data-driven approximation of Koopman…
Reinforcement Learning Compensated Extended Kalman Filter for Attitude Estimation
Yujie Tang, Liang Hu, Qingrui Zhang +1
Inertial measurement units are widely used in different fields to estimate the attitude. Many algorithms have been proposed to improve estimation performance. However, most of them…
Sparse Bayesian Deep Learning for Dynamic System Identification
Hongpeng Zhou, Chahine Ibrahim, Wei Xing Zheng +1
This paper proposes a sparse Bayesian treatment of deep neural networks (DNNs) for system identification. Although DNNs show impressive approximation ability in various fields, sev…
Probabilistic Mixture-of-Experts for Efficient Deep Reinforcement Learning
Jie Ren, Yewen Li, Zihan Ding +2
Deep reinforcement learning (DRL) has successfully solved various problems recently, typically with a unimodal policy representation. However, grasping distinguishable skills for s…
Reinforcement Learning for Orientation Estimation Using Inertial Sensors with Performance Guarantee
Liang Hu, Yujie Tang, Zhipeng Zhou +1
This paper presents a deep reinforcement learning (DRL) algorithm for orientation estimation using inertial sensors combined with magnetometer. The Lyapunov method in control theor…