National CPS PI Meeting 2013
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Abstract:
The goal of the proposed research is to identify ways to inexpensively provide specific information about energy consumption in buildings and facilitate conservation. Signal processing, machine learning, and data fusion techniques will be developed to extract actionable information from whole-building power meters and other available sensors.
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Robotic devices are excellent candidates for delivering repetitive and intensive practice that can restore functional use of the upper limbs, even years after a stroke. Rehabilitation of the wrist and hand in particular are critical for recovery of function, since hands are the primary interface with the world. However, robotic devices that focus on hand rehabilitation are limited due to excessive cost, complexity, or limited functionality.
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The electric power grid is a complex cyber-physical system (CPS), whose reliable and secure operation is of paramount importance to national security and economic vitality. There is a growing and evolving threat of cyber-based attacks, both in numbers and sophistication, on the nation's critical infrastructures. Therefore, cyber security - encompassing attack prevention, detection, mitigation, and resilience - is critical in today's power grid and the emerging smart grid.
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This project strikes a balance between performance considerations and power consumption in cyber--physical systems through algorithms that switch among different modes of operation (e.g., low--power/high--power, on/off, or mobile/static) in response to environmental conditions. The computational contribution is a hybrid optimal control framework that is connected to a number of relevant target applications where physical modeling, control design, and software architectures all constitute important components.
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The objective of this research is the development of a framework for assessing the reliability and safety of robotic surgery systems during development, field testing, and general deployment. The framework uses accurate simulations to assess pre-clinical reliability before deployment. After deployment, the framework uses data collection through online monitoring of the system as it is being used in the field, followed by analysis to obtain assessments of operational reliability and safety.
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An important area of cyber-physical systems research is the development of smart ground transportation systems due to their potentially significant impact on safety, the economy, and the environment. While technologies for smart transportation systems have advanced significantly over the last decade, there remain several challenges for the development of transportation systems that are collision free.
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Towards the development of robust cyber-physical systems, this project has developed solutions for planning and coordinating the motions of individual and networks of autonomous systems. This work is inspired by related challenges and techniques in algorithmic motion planning, multi-agent systems, sensor networks, learning and control. The focus of the project has been on the following tasks during the period 2012-2013:
