The objective of this research is to develop the theoretical foundations for understanding implicit and explicit communication within cyber-physical systems. The approach is two-fold: (a) developing new information-theoretic tools to reveal the essential nature of implicit communication in a manner analogous to (and compatible with) classical network information theory; (b) viewing the wireless ecosystem itself as a cyber-physical system in which spectrum is the physical substrate that is manipulated by heterogeneous interacting cyber-systems that must be certified to meet safety and performance objectives. The intellectual merit of this project comes from the transformative technical approaches being developed. The key to understanding implicit communication is a conceptual breakthrough in attacking the unsolved 40-year-old Witsenhausen counterexample by using an approximate-optimality paradigm combined with new ideas from sphere-packing and cognitive radio channels. These techniques open up radically new mathematical avenues to attack distributed-control problems that have long been considered fundamentally intractable. They guide the development of nonlinear control strategies that are provably orders-of-magnitude better than the best linear strategies. The keys to understanding explicit communication in cyber-physical systems are new approaches to active learning, detection, and estimation in distributed environments that combine worst-case and probabilistic elements. Beyond the many diverse applications (the Internet, the smart grid, intelligent transportation, etc.) of heterogeneous cyber-physical systems themselves, this research reaches out to wireless policy: allowing the principled formulation of government regulations for next-generation networks. Graduate students (including female ones) and postdoctoral scholars will be trained and research results incorporated into both the undergraduate and graduate curricula.

The objective of this research is to address a fundamental question in cyber-physical systems: What is the ideal structure of systems that detect critical events such as earthquakes by using data from large numbers of sensors held and managed by ordinary people in the community? The approach is to develop theory about widely-distributed sense and respond systems, using dynamic and possibly unreliable networks using sensors and responders installed and managed by ordinary citizens, and to apply the theory to problems important to society, such as responding to earthquakes. Intellectual Merit: This research develops theory and prototype implementations of community-based sense-and-respond systems that enable people help one another in societal crises. The number of participants in such systems may change rapidly; some participants may be unreliable and some may even deliberately attack systems; and the structures of networks change as crises unfold. Such systems must function in rare critical situations; so designs, analyses and tests of these systems must give confidence that they will function when the crisis hits. The proposed research will show how to design systems with organic growth, unreliable components and connections, security against rogue components, and methods of demonstrating reliability. Broader Impact: People want to help one another in a crisis. Cheap sensors, mobile phones, and laptops enable people to use information technology to help. This research empowers ordinary citizens collaborate to overcome crises. The researchers collaborate with the US Geological Service, Southern California Edison, and Microsoft, and will host 3,000 students at a seismic facility

The objective of this research is to develop a framework for the development and deployment of next-generation medical systems consisting of integrated and cooperating medical devices. The approach is to design and implement an open-source medical device coordination framework and a model-based component oriented programming methodology for the device coordination, supported by a formal framework for reasoning about device behaviors and clinical workflows. The intellectual merit of the project lies in the formal foundations of the framework that will enable rapid development, verification, and certification of medical systems and their device components, as well as the clinical scenarios they implement. The model-based approach will supply evidence for the regulatory approval process, while run-time monitoring components embedded into the system will enable "black box" recording capabilities for the forensic analysis of system failures. The open-source distribution of tools supporting the framework will enhance its adoption and technology transfer. A rigorous framework for integrating and coordinating multiple medical devices will enhance the implementation of complicated clinical scenarios and reduce medical errors in the cases that involve such scenarios. Furthermore, it will speed up and simplify the process of regulatory approval for coordination-enabled medical devices, while the formal reasoning framework will improve the confidence in the design process and in the approval decisions. Overall, the framework will help reduce costs and improve the quality of the health care.

The objective of this research is to develop a real-time operating system for a virtual humanoid avatar that will model human behaviors such as visual tracking and other sensori-motor tasks in natural environments. This approach has become possible to test because of the development of theoretical tools in inverse reinforcement learning (IRL) that allow the acquisition of reward functions from detailed measurements of human behavior, together with technical developments in virtual environments and behavioral monitoring that allow such measurements to be obtained. The central idea is that complex behaviors can be decomposed into sub-tasks that can be considered more or less independently. An embodied agent learns a policy for actions required by each sub-task, given the state information from sensori-motor measurements, in order to maximize total reward. The reward functions implied by human data can be computed and compared to those of an avatar model using the newly-developed IRL technique, constituting an exacting test of the system. The broadest impact of the project would provide a formal template for further investigations of human mental function. Modular RL models of human behavior would allow realistic humanoid avatars to be used in training for emergency situations, conversation, computer games, and classroom tutoring. Monitoring behavior in patients with diseases that exhibit unusual eye movements (e.g., Tourettes, Schizophrenia, ADHD) and unusual body movement patterns (e.g., Parkinsons), should lead to new diagnostic methods. In addition the regular use of the laboratory in undergraduate courses and outreach programs promotes diversity.

The goal of this project is to develop a novel cyber-physical system (CPS) for performing multimodal image-guided robot-assisted minimally invasive surgeries (MIS). The approach is based on: (1) novel quantitative analysis of multi-contrast data, (2) control that uses this information to maneuver conformable robotic manipulators, while adjusting on-the-fly scanning parameters to acquire additional information, and (3) human-information/machine-interfacing for comprehensive appreciation of the physical environment. The intellectual merit arises from the development of: (1) a CPS that relies on "real" and "real-time" data, minimizing parametric and abstracted assumptions, extracts and matures information from a dynamic physical system (patient and robot) by combining management of data collection (at the physical sensor site) and data analysis (at the cyber site), (2) "smart sensing", to control data acquisition based on disruptive or situation altering events, (3) control coordination by interlacing sensing, control and perception, and the incorporation of steerable tools. The societal impact arises from contributions to a leap in MIS: from "keyhole" visualization (i.e., laparoscopy) to in-situ real-time image guidance, thereby enabling a wider range of MIS. This will directly benefit patients and their families (faster recovery/reduced trauma). Economic impact arises from the cost-effectiveness of MIS to the health care system, faster patient return to the workplace, and technology commercialization. The project will integrate research and education, diversity and outreach, by enhancing current and introducing new research-intensive courses in Cyber-physical Systems, Medical Imaging and Medical Robotics, and dissemination via trans-institutional collaborations, a comprehensive web site, multimedia web-seminars, and distribution to high schools.

The objective of this research is to develop an intuitive user interface for functional electrical stimulation (FES), which uses surgically-implanted electrodes to stimulate muscles in spinal cord-injured (SCI) patients. The challenge is to enable high-level tetraplegic patients to regain the use of their own arm. The approach is to develop a multi-modal Bayesian user-intent decoder; use natural muscle synergies to generate appropriate low-dimensional muscle activation signals in a feedforward controller; develop a feedback controller to enhance the performance of the feedforward controller; and test the system with SCI patients on daily living tasks, such as reaching, grasping, and eating. The challenge problem of restoring arm use to SCI patients will lead to new design principles for cyber-physical systems interfacing neural and biological systems with engineered computation and electrical power systems. The tight integration of the proposed user interface and controller with the users own control system requires a deep understanding of biological design principles such as nested feedback loops at different time and length scales, noisy signals, parallel processing, and highly coupled neuromechanical systems. This work will lead to new technology that dramatically improves the lives of spinal cord-injured patients. These patients often have no cognitive impairment and have long life spans after injury. The goal is to enable these patients to eat, reach, and grasp nearby objects. These tasks are critical for independent living and quality of life. This work will also help train a new generation of students in human-machine interfaces at the undergraduate, graduate, and postdoctoral levels.

The objective of this research is to understand mechanisms for generating natural movements of skeletal mechanisms driven by stochastically-controlled, biologically-inspired actuators. The approach is to verify the hypothesis that the variability associated with high redundancy and the stochastic nature of the actuation is key to generating natural movements. This project seeks to: (i) develop a method to model and characterize actuator array topologies; (ii) develop a method to analyze the force variability of stochastic actuator arrays; (iii) develop an analytical method to generate movements for a robot with multiple degrees of freedom by minimizing the effect of variability; and (iv) demonstrate the validity of the approach through the development of a robotic arm driven by multiple stochastic array actuators. With respect to intellectual merit, the study of inhomogeneous stochastic actuator network topologies inspired by neuromuscular systems could find the "missing links" that bridge the gap between biological natural movements and the ones in artificial systems. Potential results could impact other research areas, including robust computer networks, robust immune systems, and redundant muscle coordination. With respect to broader impacts, a new graduate-level course provides students in engineering and science with a comprehensive and multidisciplinary education in the underlying principles, cutting-edge applications, and societal impacts of biologically-inspired robotics. Outreach activities include an interactive educational program for K-12 students and a workshop for high-school students and their mentors on robot development. International collaboration with Tokyo University of Science, Japan, will be initiated.

Proposal Title: CPS:Medium:Collaborative Research: The Foundations of Implicit and Explicit Communication in Cyberphysical Systems Institution: University of California-Berkeley Abstract Date: 07/30/09 The objective of this research is to develop the theoretical foundations for understanding implicit and explicit communication within cyber-physical systems. The approach is two-fold: (a) developing new information-theoretic tools to reveal the essential nature of implicit communication in a manner analogous to (and compatible with) classical network information theory; (b) viewing the wireless ecosystem itself as a cyber-physical system in which spectrum is the physical substrate that is manipulated by heterogeneous interacting cyber-systems that must be certified to meet safety and performance objectives. The intellectual merit of this project comes from the transformative technical approaches being developed. The key to understanding implicit communication is a conceptual breakthrough in attacking the unsolved 40-year-old Witsenhausen counterexample by using an approximate-optimality paradigm combined with new ideas from sphere-packing and cognitive radio channels. These techniques open up radically new mathematical avenues to attack distributed-control problems that have long been considered fundamentally intractable. They guide the development of nonlinear control strategies that are provably orders-of-magnitude better than the best linear strategies. The keys to understanding explicit communication in cyber-physical systems are new approaches to active learning, detection, and estimation in distributed environments that combine worst-case and probabilistic elements. Beyond the many diverse applications (the Internet, the smart grid, intelligent transportation, etc.) of heterogeneous cyber-physical systems themselves, this research reaches out to wireless policy: allowing the principled formulation of government regulations for next-generation networks. Graduate students (including female ones) and postdoctoral scholars will be trained and research results incorporated into both the undergraduate and graduate curricula. NATIONAL SCIENCE FOUNDATION Proposal Abstract Proposal:0932410 PI Name:Sahai, Anant Printed from

Objectives and approaches. The objective of this research is to create a novel Cyber-Physical System, a self-reconfiguring ?second skin orthotic sleeve? consisting of programmable materials. The orthotic sleeve, worn over one or more limbs of brain-injured individuals, may restore brain function by promoting enriched exploration of self-produced limb movements. The approach consists of three steps (1) micro-fabricating sheets with embedded sensors and muscle-like collections of force-producing actuators, (2) conducting longitudinal recordings of kicking by typically developing and preterm brain-injured infants who wear a sensing, but not actuated micro-fabricated second skin, and (3) developing biologically-inspired programming techniques to help determine an algorithm with which the second skin embedded actuators may adaptively assist the ever-changing developmental pattern of infant kicking. The technology can be applied to many mobility-impaired populations,including children and adults with brain injury, the ageing population, and injured soldiers. The project will inform basic scientific and engineering research in areas such as formation of architectural structures by large-scale multi-agent robotic systems, and self-organization of swarming small-scale agents that act autonomously in cooperation with biological systems. The multi-institutional effort of this research endeavor will positively impact undergraduate and graduate science education via explorations of the intersection of biology and computation in cyber-physical systems. Innovation, teamwork, and the value of communication are encouraged. These efforts will promote education of an American work force that is technically expert, scientifically comprehensive, and socially aware to sustain national excellence in a future increasingly based on technologically complex systems.

The objective of this research is to investigate and implement a software architecture to improve productivity in the development of rapidly deployable, robust, real-time situational awareness and response applications. The approach is based on a modular cross-layered architecture that combines a data-centric descriptive programming model with an overlay-based communication model. The cross-layer architecture will promote an efficient implementation. Simultaneously, the data-centric programming model and overlay-based communication model will promote a robust implementation that can take advantage of heterogeneous resources and respond to different failures. There is currently no high-level software architecture that meets the stringent requirements of many situational awareness and response applications. The proposed project will fill this void by developing a novel data-centric programming model that spans devices with varying computational and communication capabilities. Similarly, the overlay communication model will extend existing work by integrating network resources with the programming model. This cross-layer design will promote the implementation of efficient and robust applications. This research will benefit society by providing emergency responders with software tools that present key information in a timely fashion. This, in turn, will increase safety and reduce economic and human loss during emergencies. The productivity gains in deploying sensors and mobile devices will benefit other domains, such as field research using sensor networks. Software will be released under an open-source license to promote the use by government agencies, research institutions, and individuals. Products of this research, including the software, will be used in courses at the University of North Carolina.