19 citations · 30 across the 5 of their papers we have counts for
5 papers
Synthesize Efficient Safety Certificates for Learning-Based Safe Control using Magnitude Regularization
Haotian Zheng, Haitong Ma, Sifa Zheng +2
Energy-function-based safety certificates can provide provable safety guarantees for the safe control tasks of complex robotic systems. However, all recent studies about learning-b…
Performance-Driven Controller Tuning via Derivative-Free Reinforcement Learning
Yuheng Lei, Jianyu Chen, Shengbo Eben Li +1
Choosing an appropriate parameter set for the designed controller is critical for the final performance but usually requires a tedious and careful tuning process, which implies a s…
Feasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise Safety
Haitong Ma, Yang Guan, Shegnbo Eben Li +3
The safety constraints commonly used by existing safe reinforcement learning (RL) methods are defined only on expectation of initial states, but allow each certain state to be unsa…
Model-based Constrained Reinforcement Learning using Generalized Control Barrier Function
Haitong Ma, Jianyu Chen, Shengbo Eben Li +4
Model information can be used to predict future trajectories, so it has huge potential to avoid dangerous region when implementing reinforcement learning (RL) on real-world tasks,…
Feasibility Enhancement of Constrained Receding Horizon Control Using Generalized Control Barrier Function
Haitong Ma, Xiangteng Zhang, Shengbo Eben Li +3
Receding horizon control (RHC) is a popular procedure to deal with optimal control problems. Due to the existence of state constraints, optimization-based RHC often suffers the not…