PECTS learns dynamics and CBFs to constrain MPC trajectories probabilistically, enabling safer RL in stochastic unknown environments via sampling-based optimization.
Safe reinforcement learning using robust control barrier functions
2 Pith papers cite this work. Polarity classification is still indexing.
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PBRS-augmented RL trained in simple settings transfers zero-shot to complex UAV environments when wrapped with a CLF-CBF-QP safety filter, yielding shorter missions and formal safety guarantees.
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A Control Barrier Function-Constrained Model Predictive Control Framework for Safe Reinforcement Learning
PECTS learns dynamics and CBFs to constrain MPC trajectories probabilistically, enabling safer RL in stochastic unknown environments via sampling-based optimization.
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Zero-Shot, Safe and Time-Efficient UAV Navigation via Potential-Based Reward Shaping, Control Lyapunov and Barrier Functions
PBRS-augmented RL trained in simple settings transfers zero-shot to complex UAV environments when wrapped with a CLF-CBF-QP safety filter, yielding shorter missions and formal safety guarantees.