The terms denote engineering domains that have high CPS content.
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Many safety-critical cyber-physical systems rely on advanced sensing capabilities to react to changing
environmental conditions. However, cost-effective deployments of such capabilities have remained
elusive. Such deployments will require software infrastructure that enables multiple sensor-processing
streams to be multiplexed onto a common hardware platform at reasonable cost, as well as tools and
methods for validating that required processing rates can be maintained.
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The goal of this project is to create a scalable and robust cyber-physical system (CPS)
framework for the observation and control of the functional interdependencies between bridge
structures (stationary physical systems) and trucks (mobile physical agents). A CPS framework
(Figure 1) is being developed to monitor and control trucks within a single highway corridor to
manage the imposed loads and the consumption of structural life by trucks on highway
infrastructure including bridges. The framework begins with the installation of wireless sensing
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Security and privacy concerns in the increasingly interconnected world are receiving much attention from the research community, policymakers, and general public. However, much of the recent and on-going efforts concentrate on privacy in communication and social interactions. The advent of cyber-physical systems, which aim at tight integration between distributed computational intelligence, communication networks, physical world, and human actors, opens new possibilities for developing intelligent systems with new capabilities.
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The current lack of toolchain for high confidence testing, validation and verification of advanced, connected and automated/autonomous vehicles can impede and even entirely prevent the introduction of such vehicles into mass production. To address this challenge, this projects develops theory, methods, and tools for generating and optimizing test trajectories and data inputs that can maximize opportunities to uncover faults in both physical and cyber domain in future automotive vehicles.
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Episodic brain disorders such as epilepsy have a considerable impact on a patient's productivity and quality of life and may be life-threatening when seizures cannot be controlled with medications. We will create a second generation brain-implantable sensing and stimulating device (BISSD) based on CPS principles and practice. The BISSD will be composed of modules placed intracranially to continuously monitor brain state and vulnerability to seizure and intervene with electrical stimulation to block the development of seizure.
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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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This project aims at deriving a scalable, correct-by-construction formal design methodology for multi-robot systems that can guarantee the accomplishment of high-level team missions through automatic synthesis of local coordination mechanisms and control laws. The basic idea is to decompose the team mission into individual subtasks such that the design can be reduced to local synthesis problems for individual robots. Multidisciplinary approaches combining hybrid systems, supervisory control, regular inference and model checking are utilized to achieve this goal.
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The objective of this research is to develop the theory, hardware and computational infrastructure that will
enable automatically transforming user-defined, high-level tasks into correct, low-level perception
informed control and configurations for modular robots. Modular robots are composed of simple
individual modules with limited sensing and actuation; while each module can locomote in the
environment, connecting multiple modules in different configurations allows modular robots to perform
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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.
