An information-form surrogate simplifies sensor scheduling optimization for continuous-discrete Kalman filters with stochastic arrivals and supplies two-sided performance bounds.
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SACBFs guarantee continuous-time safety and finite-time reach-and-remain under zero-order-hold control by estimating inter-sample barrier evolution with Taylor upper bounds and adding a relaxed variant for multiple constraints.
Switch enables humanoid robots to perform agile, seamless transitions between locomotion skills via a kinematic skill graph, DRL tracking policy, and real-time graph-search scheduler.
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Switch: Learning Agile Skills Switching for Humanoid Robots
Switch enables humanoid robots to perform agile, seamless transitions between locomotion skills via a kinematic skill graph, DRL tracking policy, and real-time graph-search scheduler.