AutoSERL achieves strong performance on six real-world robot manipulation tasks using RL guided by a single demonstration via sliding-window intervention, safety recovery, and automatic termination.
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A hybrid ES-DRL controller uses VAE latent Mahalanobis OOD detection to switch between RL and ES modes for time-varying nonlinear systems.
citing papers explorer
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One Demonstration Is Enough for Real-World Robotic Reinforcement Learning
AutoSERL achieves strong performance on six real-world robot manipulation tasks using RL guided by a single demonstration via sliding-window intervention, safety recovery, and automatic termination.
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Mahalanobis-Guided Latent OOD Detection for Hybrid ES-DRL Control in Time-Varying Systems
A hybrid ES-DRL controller uses VAE latent Mahalanobis OOD detection to switch between RL and ES modes for time-varying nonlinear systems.