A two-stage Bayesian procedure propagates credible sets from a learned Hamiltonian into control barrier functions, delivering an end-to-end safety guarantee of at least 1 minus the sum of two independent credibility budgets.
Safety-critical kinematic control of robotic systems
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A CBF-based hierarchical quadratic programming framework enables flexible prioritization of safety and performance tasks for safe physical human-robot interaction, demonstrated on a real redundant robot.
citing papers explorer
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Bayesian Safety Guarantees for Port-Hamiltonian Systems with Learned Energy Functions
A two-stage Bayesian procedure propagates credible sets from a learned Hamiltonian into control barrier functions, delivering an end-to-end safety guarantee of at least 1 minus the sum of two independent credibility budgets.
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Control Barrier Functions Solved with Hierarchical Quadratic Programming for Safe Physical Human-Robot Interaction
A CBF-based hierarchical quadratic programming framework enables flexible prioritization of safety and performance tasks for safe physical human-robot interaction, demonstrated on a real redundant robot.