PECTS learns dynamics and CBFs to constrain MPC trajectories probabilistically, enabling safer RL in stochastic unknown environments via sampling-based optimization.
Guaranteed-safe MPPI through composite control barrier functions for efficient sampling in multi-constrained robotic systems
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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.