Time-Optimal Control for High-Order Chain-of-Integrators Systems with Full State Constraints and Arbitrary Terminal States (Extended Version)

1 code implementation • 13 Nov 2023 • Yunan Wang, Chuxiong Hu, Zeyang Li, Shize Lin, Suqin He, Yu Zhu

Time-optimal control for high-order chain-of-integrators systems with full state constraints and arbitrarily given terminal states remains a challenging problem in the optimal control theory domain, yet to be resolved.

Trajectory Planning

Bridging the Gap between Newton-Raphson Method and Regularized Policy Iteration

no code implementations • 11 Oct 2023 • Zeyang Li, Chuxiong Hu, Yunan Wang, Guojian Zhan, Jie Li, Shengbo Eben Li

We also show that a modified version of regularized policy iteration, i. e., with finite-step policy evaluation, is equivalent to inexact Newton method where the Newton iteration formula is solved with truncated iterations.

Robust Safe Reinforcement Learning under Adversarial Disturbances

no code implementations • 11 Oct 2023 • Zeyang Li, Chuxiong Hu, Shengbo Eben Li, Jia Cheng, Yunan Wang

To address this challenge, this paper proposes a robust safe reinforcement learning framework that tackles worst-case disturbances.

reinforcement-learning Safe Reinforcement Learning

Safe Reinforcement Learning with Dual Robustness

no code implementations • 13 Sep 2023 • Zeyang Li, Chuxiong Hu, Yunan Wang, Yujie Yang, Shengbo Eben Li

To address this issue, we propose a systematic framework to unify safe RL and robust RL, including problem formulation, iteration scheme, convergence analysis and practical algorithm design.

reinforcement-learning Reinforcement Learning (RL) +2