A particle-based probabilistic CBF framework derives finite-sample safety certificates for Gaussian state estimation uncertainty by showing that barrier increments remain sub-Gaussian under Lipschitz control-affine dynamics.
Input-to-state safety with control barrier functions
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A sliding mode controller with C3BF safety filter achieves robust trajectory tracking and moving obstacle avoidance across Ackermann, differential drive, and quadrotor platforms, validated in real experiments.
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Probabilistic Control Barrier Functions for Systems with State Estimation Uncertainty using Sub-Gaussian Concentration
A particle-based probabilistic CBF framework derives finite-sample safety certificates for Gaussian state estimation uncertainty by showing that barrier increments remain sub-Gaussian under Lipschitz control-affine dynamics.
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Sliding Mode Control for Safe Trajectory Tracking with Moving Obstacles Avoidance: Experimental Validation on Planar Robots
A sliding mode controller with C3BF safety filter achieves robust trajectory tracking and moving obstacle avoidance across Ackermann, differential drive, and quadrotor platforms, validated in real experiments.