The formalization of system engineering models and approaches.
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The broad goal of this project is to advance both the foundations and the enabling technologies in the field of human-machine systems, with a focus on exercise and rehabilitation machines.
One of the motivations of our project is the observation that advances in exercise devices are mostly seen in their haptic interfaces rather than their intrinsic capabalities. Also, our collaboration with NASA on exercise machines for astronauts has motivaed us to investigate this aspect of human-machine interaction.
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Abstract: Robustness Guided Testing and Verification for Cyber-Physical Systems
PI: Georgios Fainekos School of Computing, Informatics and Decision System Engineering, Arizona State University. E-mail: fainekos@asu.edu Website: http://www.public.asu.edu/~gfaineko
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The powertrain control problem is one of regulating the air-to-fuel ratio in an automotive engine. A series of models of such controllers, with increasing levels of sophistication and fidelity to real-world designs, have been recently proposed by Toyota researchers as challenge problems for today's verification technologies.
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Our overall aim in this project is to synthesize desired behaviors in populations of bacterial and mammalian cells. To this goal, we define the basis of a next-generation cyber-physical system (CPS) called biological CPS (bioCPS). The enabling technologies are synthetic biology and micron-scale mobile robotics. Synthetic genetic circuits for decision making and local communication among the cells are automatically synthesized using a Bio-Design Automation (BDA) workflow.
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The objective of this project is to improve the performance of autonomous systems in dynamic environments by integrating perception, planning paradigms, learning, and databases. For the next generation of autonomous systems to be truly effective in terms of tangible performance improvements (e.g., long-term operations, complex and rapidly changing environments), a new level of intelligence must be attained.
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Computer systems are increasingly coming to be relied upon to augment or replace human
operators in controlling mechanical devices in contexts such as transportation systems, chemical
plants, and medical devices, where safety and correctness are critical. A central problem is how
to verify that such partially automated or fully autonomous cyber-physical systems (CPS) are
worthy of our trust. One promising approach involves synthesis of the computer implementation
