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Adaptive Risk-Certified Event-Triggered Replanning for Dynamic Navigation
Safe navigation in dynamic environments requires robots to plan under obstacle predictions whose errors are uncertain, non-stationary, and can induce rare but safety-critical failures. Existing control-barrier-function safety filters can reject immediately unsafe controls, but they provide little gu
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