The objective of this research is to develop a comprehensive theoretical and experimental cyber-physical framework to enable intelligent human-environment interaction capabilities by a synergistic combination of computer vision and robotics. Specifically, the approach is applied to examine individualized remote rehabilitation with an intelligent, articulated, and adjustable lower limb orthotic brace to manage Knee Osteoarthritis, where a visual-sensing/dynamical-systems perspective is adopted to: (1) track and record patient/device interactions with internet-enabled commercial-off-the-shelf computer-vision-devices; (2) abstract the interactions into parametric and composable low-dimensional manifold representations; (3) link to quantitative biomechanical assessment of the individual patients; (4) facilitate development of individualized user models and exercise regimen; and (5) aid the progressive parametric refinement of exercises and adjustment of bracing devices. This research and its results will enable us to understand underlying human neuro-musculo-skeletal and locomotion principles by merging notions of quantitative data acquisition, and lower-order modeling coupled with individualized feedback. Beyond efficient representation, the quantitative visual models offer the potential to capture fundamental underlying physical, physiological, and behavioral mechanisms grounded on biomechanical assessments, and thereby afford insights into the generative hypotheses of human actions. Knee osteoarthritis is an important public health issue, because of high costs associated with treatments. The ability to leverage a quantitative paradigm, both in terms of diagnosis and prescription, to improve mobility and reduce pain in patients would be a significant benefit. Moreover, the home-based rehabilitation setting offers not only immense flexibility, but also access to a significantly greater portion of the patient population. The project is also integrated with extensive educational and outreach activities to serve a variety of communities.

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. A design and control strategy for such devices that bridges this gap is critical. The goals of the research effort are to analyze the properties and role of passive dynamics, defined by joint stiffness and damping, in the human hand and wrist during grasping and manipulation, and then mimic such properties in a wrist-hand exoskeleton for stroke rehabilitation. The project will culminate with device testing in collaboration with rehabilitation clinicians. A significant problem in robotic rehabilitation is how to provide assisted movement to the multiple degrees of freedom of the hand in order to restore motor coordination and function, with a system that is practical for deployment in a clinical environment. Armed with a clearer understanding of the mechanisms underlying passive dynamics and control of systems exhibiting such behavior, this project will inform the design of more effective wrist/hand rehabilitation devices that are feasible for clinical use. In addition, the proposed project will create a unique interdisciplinary environment enabling education, training, and co-advising of graduate students, undergraduate research, and significant and targeted outreach activities to underrepresented groups in science and engineering.

This project develops a framework for design automation of cyber-physical systems to augment human interaction with complex systems that integrate across computational and physical environments. As a design driver, the project develops a Body/Brain Computer Interface (BBCI) for the population of functionally locked-in individuals, who are unable to interact with the physical world through movement and speech. The BBCI will enable communication with other humans through expressive language generation and interaction with the environment through robotic manipulators. Utilizing advances in system-level design, this project develops a holistic framework for design and implementation of heterogeneous human-in-the-loop cyber-physical systems composed of physically distributed, networked components. It will advance BBCI technology by incorporating context aware inference and learning of task-specific human intent estimation in applications involving semi-autonomous robotic actuators and an efficient wireless communication framework. The results of this project are expected to significantly speed up the design of complex cyber-physical systems. By accelerating the path from idea to prototype, this work shortens the time frame of and cost of development for assistive technology to improve the quality-of-life for functionally locked-in individuals. This project establishes an open prototyping platform and a design framework for rapid exploration of other novel human-in-the-loop applications. The open platform will foster undergraduate involvement in cyber-physical systems research, building confidence and expertise. In addition, new activities at the Museum of Science in Boston will engage visitors to experiment with systematic design principles in context of a brain computer interface application, while offering learning opportunities about basic brain functions.

Holonic Multi-Agent Control of Intelligent Power Distribution Systems This project will demonstrate a Holonic Multiagent System Architecture capable of adaptively controlling future electrical power distribution systems (PDS), which are expected to include a large number of renewable power generators, energy storage devices, and advanced metering and control devices. The project will produce a general, extensible, and secure cyber architecture based on holonic multiagent principles to support adaptive PDS. It will produce new analytical insights to quantify the impact of information delay, quality and flow on the design and analysis of the PDS architecture. Finally, it will develop a novel approach to automating PDS with high penetration of distributed renewable resources for higher efficiency, reliability, security, and resiliency. The complex nature of future PDS will require them to adapt reactively and proactively to normal and anomalous modes of operation. The architecture produced by this project will be capable of optimizing performance and maintaining the system within operating limits during normal and minor events, such as cloud cover that reduces solar panels output. The architecture will also allow the operation of a distribution system as an island in emergencies, such as hurricanes/earthquakes, grid failures, or terrorist acts. The project will inspire future engineers via a simulation that will allow students to inject faults, failures, and weather events to see how an intelligent PDS will respond. These activities will combine cyber- and physical expertise, thus creating a workforce prepared for tomorrow?s cyber-physical system challenges. Existing university programs will be used to involve under-represented minorities and U.S. veterans in the project.

The national transmission networks that deliver high voltage electric power underpin our society and are central to the ongoing transformation of the American energy infrastructure. Transmission networks are very large and complicated engineering systems, and "keeping the lights on" as the transformation of the American energy infrastructure proceeds is a fundamental engineering challenge involving both the physical aspects of the equipment and the cyber aspects of the controls, communications, and computers that run the system. The project develops new principles of cyber-physical engineering by focusing on instabilities of electric power networks that can cause blackouts. It proposes novel approaches to analyze these instabilities and to design cyber-physical control methods to monitor, detect, and mitigate them. The controls must perform robustly in the presence of variability and uncertainty in electric generation, loads, communications, and equipment status, and during abnormal states caused by natural faults or malicious attacks. The research produces cyber-physical engineering methodologies that specifically help to mitigate power system blackouts and more generally show the way forward in designing robust cyber-physical systems in environments characterized by rich dynamics and uncertainty. Education and outreach efforts involve students at high school, undergraduate, and graduate levels, as well as dissemination of results to the public and the engineering and applied science communities in industry, government and universities.

This project takes the paradigm of cloud computing developed in the cyber-world and puts it into the physical world, to create a cyber-physical computing cloud, SAM-C. Unlike conventional cloud computing, SAM-C servers move in space, meaning, they are vehicles with physical constraints. The server vehicles also have sensors and actuators to create a way to re-organize mobile sensor networks in the paradigm of cloud computing. The project envisions an industry offering sensing as a service provided by the cloud. To enable this new service, the project extends the virtual machine instance fundamental to cloud computing with one new property -- virtual speed. The research terms this augmented entity a virtual vehicle and develops the theories, algorithms and protocols to realize many virtual vehicles over a network of real vehicle servers at scale. This research impacts the cloud computing industry by providing tools and theories it can use to leverage the many possible mobile server hosts in our society, e.g., cars, planes, people, and emerging vehicles like Unmanned Air Vehicles or drifters. It impacts mobile sensor networks by shifting them from an artifact built for an application to a service provided by a cloud. The inter-disciplinary research team spanning computer science, civil, and mechanical engineering impacts graduate and undergraduate teaching in systems, computer science, and control theory. The project guides K-12 students to build simple electric airplanes with sensors for greenhouse gas measurement thereby introducing young users of computation to cyber-physical cloud computing.

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. A design and control strategy for such devices that bridges this gap is critical. The goals of the research effort are to analyze the properties and role of passive dynamics, defined by joint stiffness and damping, in the human hand and wrist during grasping and manipulation, and then mimic such properties in a wrist-hand exoskeleton for stroke rehabilitation. The project will culminate with device testing in collaboration with rehabilitation clinicians. A significant problem in robotic rehabilitation is how to provide assisted movement to the multiple degrees of freedom of the hand in order to restore motor coordination and function, with a system that is practical for deployment in a clinical environment. Armed with a clearer understanding of the mechanisms underlying passive dynamics and control of systems exhibiting such behavior, this project will inform the design of more effective wrist/hand rehabilitation devices that are feasible for clinical use. In addition, the proposed project will create a unique interdisciplinary environment enabling education, training, and co-advising of graduate students, undergraduate research, and significant and targeted outreach activities to underrepresented groups in science and engineering.

The national transmission networks that deliver high voltage electric power underpin our society and are central to the ongoing transformation of the American energy infrastructure. Transmission networks are very large and complicated engineering systems, and "keeping the lights on" as the transformation of the American energy infrastructure proceeds is a fundamental engineering challenge involving both the physical aspects of the equipment and the cyber aspects of the controls, communications, and computers that run the system. The project develops new principles of cyber-physical engineering by focusing on instabilities of electric power networks that can cause blackouts. It proposes novel approaches to analyze these instabilities and to design cyber-physical control methods to monitor, detect, and mitigate them. The controls must perform robustly in the presence of variability and uncertainty in electric generation, loads, communications, and equipment status, and during abnormal states caused by natural faults or malicious attacks. The research produces cyber-physical engineering methodologies that specifically help to mitigate power system blackouts and more generally show the way forward in designing robust cyber-physical systems in environments characterized by rich dynamics and uncertainty. Education and outreach efforts involve students at high school, undergraduate, and graduate levels, as well as dissemination of results to the public and the engineering and applied science communities in industry, government and universities.

This project addresses the impact of the integration of renewable intermittent generation in a power grid. This includes the consideration of sophisticated sensing, communication, and actuation capabilities on the system's reliability, price volatility, and economic and environmental efficiency. Without careful crafting of its architecture, the future smart grid may suffer from a decrease in reliability. Volatility of prices may increase, and the source of high prices may be more difficult to identify because of undetectable strategic policies. This project addresses these challenges by relying on the following components: (a) the development of tractable cross-layer models; physical, cyber, and economic, that capture the fundamental tradeoffs between reliability, price volatility, and economic and environmental efficiency, (b) the development of computational tools for quantifying the value of information on decision making at various levels, (c) the development of tools for performing distributed robust control design at the distribution level in the presence of information constraints, (d) the development of dynamic economic models that can address the real-time impact of consumer's feedback on future electricity markets, and finally (e) the development of cross-layer design principles and metrics that address critical architectural issues of the future grid. This project promotes modernization of the grid by reducing the system-level barriers for integration of new technologies, including the integration of new renewable energy resources. Understanding fundamental limits of performance is indispensable to policymakers that are currently engaged in revamping the infrastructure of our energy system. It is critical that we ensure that the transition to a smarter electricity infrastructure does not jeopardize the reliability of our electricity supply twenty years down the road. The educational efforts and outreach activities will provide multidisciplinary training for students in engineering, economics, and mathematics, and will raise awareness about the exciting research challenges required to create a sustainable energy future.

This project integrates digital microfluidics with thin-film photodetectors and control software to realize DNA target sensing using fluorescence. This cyberphysical vision is being realized through tight coupling between physical components, the microfluidic platform and miniaturized sensors, and cyber components, software for control, decision-making, and adaptation. Such a level of integration, decision, and controlled reconfigurability is a significant step forward in clinical diagnostics using digital microfluidic biochips. Topics being investigated include: (i) silicon-based digital microfluidics and integration of optical sensors; (ii) closed-loop operation and run-time optimization under software control; (iii) decision-tree architectures, adaptive reconfiguration, and error recovery. A complete testbed is being developed for nucleic acid identification on a fabricated chip with detection sites. Cyberphysical system integration will transform biochip use, in the same way as compilers and operating systems revolutionized computing, and design automation revolutionized chip design. Benefits to society include the potential to transform personalized medicine, home diagnostics, and portable diagnostics. Integration of digital microfluidics, optical sensing, and software control has the potential to create systems that can be used by any person, regardless of sample preparation skill. One example is the identification of bacterial DNA associated with bacterial blood infection (sepsis), which results in death if not diagnosed early (this is in the top 10 causes of death in the US). Students are being trained through a Senior Design course to understand the design