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Automotive cyber-physical systems will need to address self-parking, advanced steering control, hazardous situation recovery, limited autonomous driving, and even more complex tasks in the coming decades. Verification of the safe behavior of these tasks for multiple vehicle configurations (weight, wheelbase, front/rear/all-wheel drive, etc.) will require significant advancements in the computational theory, as well as new approaches to compose behaviors and computational constraints with hybrid control theory and system modeling.
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This collaborative research project examines the role of software synthesis for monitoring and planning of autonomous sensors evolving on tidally forced rivers. The goal of the sensors is the coordinated sampling of currents and salinity to reconstruct the distributed state of the river. This project integrates the development of theory for the coordination of autonomous agents in motion-constrained environments, and of algorithms to perform motion planning tasks, with software tools for design, analysis, and code synthesis for implementation, as well as inverse modeling (i.e.
