3 papers
cs.LG2026
Nightmare Dreamer: Dreaming About Unsafe States And Planning Ahead
Oluwatosin Oseni, Shengjie Wang, Jun Zhu +1
Reinforcement Learning (RL) has shown remarkable success in real-world applications, particularly in robotics control. However, RL adoption remains limited due to insufficient safe…
cs.RO2023
DexCatch: Learning to Catch Arbitrary Objects with Dexterous Hands
Fengbo Lan, Shengjie Wang, Yunzhe Zhang +5
Achieving human-like dexterous manipulation remains a crucial area of research in robotics. Current research focuses on improving the success rate of pick-and-place tasks. Compared…
cs.RO2023
A Policy Optimization Method Towards Optimal-time Stability
Shengjie Wang, Fengbo Lan, Xiang Zheng +5
In current model-free reinforcement learning (RL) algorithms, stability criteria based on sampling methods are commonly utilized to guide policy optimization. However, these criter…