Guaranteeing safe behavior is a critical component of translating autonomous systems from a laboratory setting to real-world environments. With this as motivation, this talk will present a safety-critical approach to the control of nonlinear systems. To this end, a unified nonlinear control framework for realizing dynamic behaviors will be presented. Underlying this approach is an optimization-based control paradigm leveraging control barrier functions that guarantee safety (represented as forward set invariance). The impact of this paradigm will be considered in the context of autonomous systems, and the application of these ideas will be demonstrated experimentally on a wide variety of robotic systems. Finally, the realization of safety-critical control in the context of automotive systems will be considered with a view toward autonomous vehicle fleets.
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