The most compelling problem confronting detection of nuclear material in a large area is the level of manifest uncertainty. Furthermore, detection and localization problems involve nontrivial and nonlinear non-convex optimization often stuck at local minima. This project develops fundamentally new techniques by using cheap detectors for rough detection and localization, placing detectors to expunge local minima, achieving fast distributed localization with reduced communication overheads, simultaneously localizing multiple sources and optimally placing detectors and assisting in their autonomous self-organization. There is a growing recognition of the inadequacy of current capabilities with respect to nuclear material detection and localization in public events and areas. This project develops an integrated cyber-physical system for public protection against nuclear and radiological threats. Clearly the project addresses a national security issue. If successful, the contribution and results of the project likely open a new framework for detection or monitoring in a large area using a wireless detector network. One of the key aspects of this project is the inter-disciplinary training of our graduate and undergraduate students including female and minority students in the areas of signal processing, statistical methods, modeling and performance analysis. K-12 students are also targeted through the First competition and Project-Lead-The-Way that connects the College of Engineering at the University of Iowa to almost all high school students in Iowa. It is expected that the project will generate enthusiasm and interests in science, mathematics and engineering for high school students.

Autonomous navigation in unknown and dynamic environments has been a major challenge for synthetic mobile robotic agents. On the other hand, insects can easily solve such complex navigational problems and demonstrate remarkably stable and optimized locomotion skills in almost any environment. This project aims to develop a mobile sensor network where insects are used as mobile biological-robotic (biobotic) nodes. Insects, in fact, build a "natural" sensor network through the use of their biological sensing organs and release of chemical, mechanical and optical cues to communicate the information to the rest of the group. In the scope of this project, a novel cyber-physical communication network will be established among the individual insect in addition to the aforementioned natural one. For this, insects will be equipped with synthetic electronic sensors to sense additional cues, neuromuscular stimulation systems to direct the control of the insect and microcontrollers with radios to establish an RF link between the insects. This novel network will enable operation of insect biobots in complicated and uncertain dynamic environments for applications such as environmental sensing and search-and-rescue operations after natural disasters. The unique interdisciplinary nature of this project will help engineers to reach to younger generations and train them to be able to look at engineering problems from a cyberphysical systems point of view. Planned activities include development of lab modules and demos by undergraduate and graduate students to teach K-12 students and their teachers through our on-going collaborations with educational partners. These demos will also be instrumental during nation level efforts to promote graduate education to underrepresented minority students.

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.

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.

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.