3 papers
cs.LG2026
Safe Online Learning via Smooth Safety-Structured Policy Composition
Hongpeng Cao, Liqun Zhao, Yuliang Gu +3
Safe online reinforcement learning requires policies to respect safety constraints while maintaining smooth optimization dynamics. Existing approaches typically rely on either stri…
eess.SY2025
Constrained Diffusers for Safe Planning and Control
Jichen Zhang, Liqun Zhao, Antonis Papachristodoulou +1
Diffusion models have shown remarkable potential in planning and control tasks due to their ability to represent multimodal distributions over actions and trajectories. However, en…
eess.SY2025
Opt-ODENet: A Neural ODE Framework with Differentiable QP Layers for Safe and Stable Control Design (longer version)
Keyan Miao, Liqun Zhao, Han Wang +2
Designing controllers that achieve task objectives while ensuring safety is a key challenge in control systems. This work introduces Opt-ODENet, a Neural ODE framework with a diffe…