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.

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 computing landscape is a richly-heterogeneous space including both fixed and mobile nodes with a large variety of sensing, actuation and computational capabilities (including mobile devices, home electronics, taxis, robotic drones, etc.). Cyber-physical applications built on these devices have the potential to gather data on, analyze, and adapt to or control a range of environments. The challenge, however, is that Cyber-Physical Systems (CPSs) are difficult to program, and even more difficult to incorporate from one deployment to another, or to dynamically manage as nodes availability changes. Thus, CPS applications are too often programmed in a brittle fashion that impedes their ability to efficiently use available compute/sense/actuate resources beyond a one-shot deployment. In response, this project is improving CPS design and control in four primary thrusts. First, the project is developing CPSISA, an abstraction layer or intermediate representation to facilitate CPS applications expressing their compute/sense/actuate requirements to lower-level mapping and management layers. Second, the project is exploring methods of providing a Device Attribute Catalog (DAC) that summarizes a region?s available CPS nodes and their capabilities. Third, this research is improving and exploiting the ability to model, predict, and control the mobility of CPS nodes. When some CPS nodes are mobile, the accuracy and performance of a CPS application fundamentally is a function of where nodes will be positioned at any moment in time. This work exploits both static statistical coverage analysis and dynamic prediction and interpolation. Fourth, using CPSISA, DAC, and other resources as input, the team is developing tools to statically or dynamically optimize mappings of CPS applications onto available resources. To test ideas in a detailed and concrete manner, two applications are being studied and deployed. First, the FireGuide application for emergency response assistance uses groups of mobile/robotic nodes for guiding first responders in building fires. Second, a Regional Traffic Management (RTM) application demonstrates ideas at the regional level and will explore CPS scenarios for automobile traffic sensing and dynamic toll pricing. The proposed research program has the potential for broad societal impact. Studies that improve how building emergencies are handled will improve emergency response safety both for occupants and for first responders around the country. Likewise, the deployment plans regarding regional traffic management will improve traffic patterns, fuel efficiency and quality-of-life for commuters across the United States. The research team is distributing the CPSISA, CPSMap, and CPSDyn software frameworks to allow other researchers and developers to make use of them. Extensive industry collaborations foster effective technology transfer. Finally, the project continues and broadens the PIs? prior track records for undergraduate research advising and for mentoring women students and members of under-represented minority groups.

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.

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.

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.