This project will construct a wireless network of animal-borne embedded devices that will be deployed and tested in a biologically-relevant application. The networked devices will provide not only geo-location data, but also execute cooperative strategies that save battery-life by selectively recording bandwidth-intensive audio and high-definition video footage of occurrences of animal group behavior of interest, such as predation. This project comprises three concurrent and interdependent research themes. The first is the investigation of methods to design and analyze the performance of distributed algorithms that implement autonomous decisions at the mobile agents, subject to communication and computational constraints. The second will pursue data-driven fundamental research on the modeling of animal group motion and will promote a formal understanding of the mechanisms of social interaction. The third is centered on the investigation of methods for hardware integration to build distributed networks of embedded devices that are capable of executing the newly developed algorithms, subject to power and weight constraints. The results and experience gained in this project will guide the development of effective autonomous systems for the monitoring and protection of endangered species. This project will create undergraduate and graduate research opportunities at all participating institutions, expanding on an existing collaboration between the University of Maryland, Princeton University, and the National Geographic Society. There is the potential for using wide-reaching media resources to disseminate the results of this project to a broad audience. This may contribute to attracting more students to engineering and science.

A CPS is a system in which computer-based (cyber) technology is combined with all kinds of physical systems, such as planes and robotic-surgeons. CPSs require integration (in industry and academia) of different types of knowledge from many different domains. CPSs are built from often inaccurate, undependable components, and operate in harsh and unpredictable environments. The cyber domain, interfaces, and the physical domain are tightly interwoven and networked (distributed) and hence cannot be designed and optimized individually. The goal of this project is to create a general CPS design-science that makes the design of every CPS simpler, faster, and more dependable, while at the same time reducing the cost and the required expertise level. This project gives rise to a unified theory that can allow for specification, modeling, design, optimization, and verification of CPSs on different levels of design abstraction and different steps of projection, even across boundaries between varied technologies. The project does bridge the gap between the continuous-time physical domain and the discrete timed cyber system. This project has a broad and profound impact in scientific, engineering, industrial, and academic communities. By enabling a fundamentally efficient design of CPSs, the most limiting bottleneck in design technology is eliminated, paving the way for many new applications and jobs with significant economic and social impact. This project contributes to the on-line educational endeavors currently underway, allowing cross education in different disciplines of complex CPS and speeding up development of new CPS programs in engineering and computer science.

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.

The CrAVES project seeks to lay down intellectual foundations for credible autocoding of embedded systems, by which graphical control system specifications that satisfy given open-loop and closed-loop properties are automatically transformed into source code guaranteed to satisfy the same properties. The goal is that the correctness of these codes can be easily and independently verified by dedicated proof checking systems. During the autocoding process, the properties of control system specifications are transformed into proven assertions explicitly written in the resulting source code. Thus CrAVES aims at transforming the extensive safety and reliability analyses conducted by control system engineers, such as those based on Lyapunov theory, into rigorous, embedded analyses of the corresponding software implementations. CrAVES comes as a useful complement to current static software analysis methods, which it leverages to develop independent verification systems. Computers and computer programs used to manage documents and spreadsheets. They now also interact with physical artifacts (airplanes, power plants, automobile brakes and robotic surgeons), to create Cyber-Physical Systems. Software means complexity and bugs - bugs which can cause real tragedy, far beyond the frozen screens we associate with system crashes on our current PCs. Software autocoding is becoming the de facto recommended practice for many safety-critical applications. CrAVES aims to evolve this towards higher standards of quality and reduced design times and costs. Rigorous, mathematical arguments supporting safety-critical functionalities are the cornerstone of CrAVES. Collaborative programs involving high-school teachers will encourage the transmission of this message to STEM education in high-schools through university programs designed for that purpose.

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.

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.

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 aims to develop a computational framework and a physical platform for enabling dense networks of micro-robotic swarms for medical applications. The approach relies on a new stochastic framework for design and analysis of dense networks, as well as new fabrication and characterization methods for building and understanding bacteria propelled micro-robotic swarms. This project enhances the CPS science beyond passive networks of millimeter-scale bio-implantable devices with active networks of micro-robotic swarms that could be more effective in combating various critical diseases with minimal impact on the human body. Three major research objectives are proposed in this project: 1) Statistical physics inspired approach to the modeling and analysis of dense networks of swarms: The theory envisioned for characterizing the dynamics of dense networks of swarms aims at achieving ?beyond Turing? computation via dense networks, designing autonomous reliable communication protocols for dense networks, and estimating and controlling their performance; 2) Fabrication and steering of swarms of bacteria propelled swimming micro-robots: Large numbers of both chemotactic and magnetotactic bacteria integrated micro-robotic bodies will be fabricated using self-assembly and micro/nano-fabrication methods. Chemotaxis and magnetotaxis will be respectively used as passive and active steering mechanisms for navigating the swarms of micro-robots in small spaces to perform specified tasks; 3) Characterization of the behavior and control of bacteria propelled micro-robotic swarms: To validate and fine tune the proposed computational models, the motion and behavior of single and large numbers of bacteria propelled micro-robots will be characterized using optical and other microscopy methods. Intellectual Merit: The research breakthrough proposed herein consists of building a new physical platform for micro-robotic swarms by using attached bacteria as on-board actuators and chemotaxis and magnetotaxis as passive and active steering control methods, and developing a new computational dense network framework for designing and analyzing such stochastic micro-robotic swarms. The statistical computational framework to be developed in this study will improve understanding of swarming behavior and control of large numbers of bacteria propelled micro-robots. This framework offers an integrated approach towards CPS design that is meant to operate under uncertainty conditions, yet be able to succeed in performing a specified task through self-organization and collective behavior. This bottom-top approach is meant to improve the theoretical foundations of the current computational models of CPS. Broader Impacts: The resulting computational framework and the physical platform could be adapted to a wide range of different stochastic dense network systems ranging from migration of cancer cell populations or dynamics of virus populations to immune system support and modeling. The proposed swarms of bacteria integrated micro-robots have potential future applications in health-care for the diagnosis of diseases and targeted drug delivery inside the stagnant or low velocity fluids of the human body or the medical diagnosis inside lab-on-a-chip microfluidic devices. Such health-care applications could improve the welfare of our society. To foster learning and training of next generation CPS workforce, the PIs plan to emphasize a cross-disciplinary approach to teaching topics that are usually offered in disjoint tracks. The PIs will integrate the CPS research activities in this study into their newly developed courses, and they will also teach one of these courses jointly. As a joint international educational activity, a three-day Summer School will be held alternately in US and Europe every year on various CPS topics related to our project. This will help building a strong international CPS community and training US and European students in CPS topics. The PIs will present the research results of this project to children, K-12 students, K-12 teachers, IEEE and ACM student members, and college students inside and outside of USA through public lectures. This project and the Sloan Foundation will support underrepresented and minority graduate students in the project. Moreover, underrepresented minority undergraduate students will be trained through the CMU ICES summer outreach program called The SURE Thing and the NSF REU program.

In many important situations, analytically predicting the behavior of physical systems is not possible. For example, the three dimensional nature of physical systems makes it provably impossible to express closed-form analytical solutions for even the simplest systems. This has made experimentation the primary modality for designing new cyber-physical systems (CPS). Since physical prototyping and experiments are typically costly and hard to conduct, "virtual experiments" in the form of modeling and simulation can dramatically accelerate innovation in CPS. Unfortunately, major technical challenges often impede the effectiveness of modeling and simulation. This project develops foundations and tools for overcoming these challenges. The project focuses on robotics as an important, archetypical class of CPS, and consists of four key tasks: 1) Compiling and analyzing a benchmark suite for modeling and simulating robots, 2) Developing a meta-theory for relating cyber-physical models, as well as tools and a test bed for robot modeling and simulation, 3) Validating the research results of the project using two state-of-the-art robot platforms that incorporate novel control technologies and will require novel programming techniques to fully realize their potential 4) Developing course materials incorporating the project's research results and test bed. With the aim of accelerating innovation in a wide range of domains including stroke rehabilitation and prosthetic limbs, the project is developing new control concepts and modeling and simulation technologies for robotics. In addition to new mathematical foundations, models, and validation methods, the project will also develop software tools and systematic methods for using them. The project trains four doctoral students; develops a new course on modeling and simulation for cyber-physical systems that balances both control and programming concepts; and includes an outreach component to the public and to minority-serving K-12 programs.

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.