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cs.RO2026
Certifiable Safe Model-Based Reinforcement Learning with Control-Affine Dynamics Approximation
Hao Zhou, Yanze Zhang, Cameron Reid +1
Safe model-based reinforcement learning (RL) often bridges control-theoretic analysis and RL for robots to safely explore (partially) unknown system dynamics while deriving control…
cs.RO2025
Computationally and Sample Efficient Safe Reinforcement Learning Using Adaptive Conformal Prediction
Hao Zhou, Yanze Zhang, Wenhao Luo
Safety is a critical concern in learning-enabled autonomous systems especially when deploying these systems in real-world scenarios. An important challenge is accurately quantifyin…
cs.RO2024
Safety-Critical Control with Uncertainty Quantification using Adaptive Conformal Prediction
Hao Zhou, Yanze Zhang, Wenhao Luo
Safety assurance is critical in the planning and control of robotic systems. For robots operating in the real world, the safety-critical design often needs to explicitly address un…