Abstract: Control barrier functions (CBFs) provide a rigorous framework for enforcing safety in control-affine systems by ensuring system states remain within predefined safe sets. However, practical ...
Abstract: Learning-based methods have gained popularity for training candidate Control Barrier Functions (CBFs) to satisfy the CBF conditions on a finite set of sampled states. However, since the CBF ...
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