The Safe Autonomous Systems Lab

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Our lab works to provide scalable safety assurances and control policies based on available models and data about the system and environment. These techniques must be able to quickly adapt to unexpected changes and new information in the autonomous system or the environment. We use tools from optimal control theory and dynamics games, machine learning, and cognitive science to develop new techniques for safety and efficiency in autonomous systems. These techniques are backed by both rigorous theory and physical testing on robotic platforms.
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