This proposed CPS project aims to enable intelligent telesurgery in which a surgeon, or a distributed team of surgeons, can work on tiny regions in the body with minimal access. The University of Washington will expand an existing open surgical robot testbed, and create a robust infrastructure for cyber-physical systems with which to extend traditional real-time control and teleoperation concepts by adding three new interfaces to the system: networking, intelligent robotics, and novel non-linear controllers. Intellectual Merit: This project aims to break new ground beyond teleoperation by adding advanced robotic functions. Equally robust and flexible networking, high-level interfaces, and novel controllers will be added to the existing sytsem. The resulting system will be an open architecture and a substrate upon which many cyber-physical system ideas and algorithms will be tested under realistic conditions. The platforms proven physical robustness will permit rigorous evaluation of results and the open interfaces will encourage collaboration and sharing of results. Broader Impacts: We expect the results to enable new research in multiple ways. First, the collaborators such as Johns Hopkins, U.C. Santa Cruz, and several foreign institutions will be able to remotely connect to new high level interfaces provided by this project. Second, for the first time a robust and completely open surgical telerobot will be available for research so that CPS researchers do not need to be limited to isolated toy problems but instead be able to prototype advanced surgical robotics techniques and evaluate them in realistic contexts including animal procedures.

The objective of this research is the transformation from static sensing into mobile, actuated sensing in dynamic environments, with a focus on sensing in tidally forced rivers. The approach is to develop inverse modeling techniques to sense the environment, coordination algorithms to distribute sensors spatially, and software that uses the sensed environmental data to enable these coordination algorithms to adapt to new sensed conditions. This work relies on the concurrent sensing of the environment and actuation of those sensors based on sensed data. Sensing the environment is approached as a two-layer optimization problem. Since mobile sensors in dynamic environments may move even when not actuated, sensor coordination and actuation algorithms must maintain connectivity for the sensors while ensuring those sensors are appropriately located. The algorithms and software developed consider the time scales of the sensed environment, as well as the motion capabilities of the mobile sensors. This closes the loop from sensing of the environment to actuation of the devices that perform that sensing. This work is addresses a challenging problem: the management of clean water resources. Tidally forced rivers are critical elements in the water supply for millions of Californians. By involving students from underrepresented groups, this research provides a valuable opportunity for students to develop an interest in engineering and to learn first hand about the role of science and engineering in addressing environmental issues.

The goal of the proposed research is to identify ways to inexpensively provide specific information about energy consumption in buildings and facilitate conservation. Signal processing, machine learning, and data fusion techniques will be developed to extract actionable information from whole-building power meters and other available sensors. The main objectives are: (a) to create a framework for obtaining disaggregated, appliance-specific feedback about electricity consumption in a building by extracting high-value information from low-cost data sources; and (b) to investigate and develop data mining and machine learning algorithms for making use of appliance-specific electricity data, in order to provide users with recommendations on how to optimize their energy consumption and understand the effects of their energy-related decisions. A series of residential buildings in Pittsburgh, PA will serve as a test-bed for evaluating and validating our proposed approach. Blueroof Technologies, a non-profit corporation located in McKeesport, PA that researches, develops and provides affordable senior-citizen housing with integrated sensor networks and building automation systems, will provide access to their Research Cottages for this project. Similarly, Robert Bosch LLC, a leading global provider of consumer goods and building technology, will provide additional technical research assistance and expertise. The main scientific merit of the project is the development of a framework for evaluating energy-use-disaggregation methods according to their value for promoting energy conservation. The resulting data sets will be large enough to produce significant conclusions about the feasibility and effectiveness of the technology, and allow for the development of new models about the trends and patterns of appliance usage in buildings. Broader impacts of this research include providing a foundation for future cyber-physical systems by inexpensively obtaining real-time appliance-level data. Such data can be used to help reduce the energy consumption of buildings by revealing the relationship between users' behavior and electricity consumption in buildings. The proposed industry-university collaborative research effort with Bosch will ensure that the technology and scientific contributions are steered toward innovative solutions that are practical for adoption in the market. Furthermore, the project will have significant diversity contributions by attracting minority students through collaboration with the University of Maryland Eastern Shore, a land-grant, historically black college with a diverse student body. Finally, a series of planned industry seminars, workshops and the publication of journal articles will allow further dissemination of the work.

The objective of this research is to develop abstractions by which the controlled process and computation state in a cyber-physical system can both be expressed in a form that is useful for decision-making across real-time task scheduling and control actuation domains. The approach is to quantify the control degradation in terms of response time, thereby tying computer responsiveness to the controlled process performance and use such cost functions to effectively manage computational resources. Similarly, control strategies can be adjusted so as to be responsive to computational state. Unmanned aircraft will be used as vehicles to demonstrate our approach. The intellectual merit of this research is that it takes disparate fields, control and computation, and builds formal abstractions in both the computation-to-control and control-to-computation directions. These abstractions are grounded in terms of physical reality (e.g., time, fuel, energy) and encapsulate in a form comprehensible and meaningful to each domain, the relevant attributes of the other domain. This research is important because cyber-physical systems are playing an increasing role in all walks of life. It will allow design approaches to be systematic and efficient rather than ad hoc. It is based on a large body of our prior work that has begun to successfully bridge the representational and algorithmic gap that separates the control and computer science & engineering communities. Dissemination of results will be by means of courses in our universities, instructional materials, research and tutorial publications and industry collaboration (e.g., General Motors R&D). The plan is to hire minority/female students.

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 investigate and develop methods and tools for the analysis and verification of cyber-physical systems. The approach is to augment the methods and tools that have been developed at the University of Utah and the University of South Florida for modeling and verification of asynchronous and analog/mixed-signal circuits to address challenges in cyber-physical system verification. This research will develop a unified framework with methods and tools which include an integrated formalism to comprehensively model discrete/continuous, functional/timing, synchronous/asynchronous, and deterministic/stochastic behavior. These tools will also include algorithms to analyze behavior and verify that it satisfies the correctness requirements on functionality, timing, and robustness. Finally, they will include abstraction and compositional reasoning approaches to enable large systems to be analyzed and verified efficiently. Since cyber-physical systems are becoming ubiquitous, improvements in such systems such as higher reliability, better fault-tolerance, improved performance, and lower design costs will have tremendous positive impact on society. Results from this research will be transferred to the cyber-physical systems community and other application domains by both publishing papers in related conferences and journals as well as by freely distributing tools via the Internet. Both graduate and undergraduate students will be engaged in this multi-institutional research where they will be exposed to the latest research in formal and probabilistic analysis. Early involvement of undergraduate students may help encourage them to attend graduate school. This research project will also recruit underrepresented and female students to allow it to reach broader audiences.

The objective of this research is to investigate and develop methods and tools for the analysis and verification of cyber-physical systems. The approach is to augment the methods and tools that have been developed at the University of Utah and the University of South Florida for modeling and verification of asynchronous and analog/mixed-signal circuits to address challenges in cyber-physical system verification. This research will develop a unified framework with methods and tools which include an integrated formalism to comprehensively model discrete/continuous, functional/timing, synchronous/asynchronous, and deterministic/stochastic behavior. These tools will also include algorithms to analyze behavior and verify that it satisfies the correctness requirements on functionality, timing, and robustness. Finally, they will include abstraction and compositional reasoning approaches to enable large systems to be analyzed and verified efficiently. Since cyber-physical systems are becoming ubiquitous, improvements in such systems such as higher reliability, better fault-tolerance, improved performance, and lower design costs will have tremendous positive impact on society. Results from this research will be transferred to the cyber-physical systems community and other application domains by both publishing papers in related conferences and journals as well as by freely distributing tools via the Internet. Both graduate and undergraduate students will be engaged in this multi-institutional research where they will be exposed to the latest research in formal and probabilistic analysis. Early involvement of undergraduate students may help encourage them to attend graduate school. This research project will also recruit underrepresented and female students to allow it to reach broader audiences.

This objective of this proposal is to improve the management of the air traffic system, a cyber-physical system where the need for a tight connection between the computational algorithms and the physical system is critical to safe, reliable and efficient performance. The approach is based on an adaptive multi-agent coordination algorithm with a particular emphasis on the systematic selection of the agents, their actions and the agents' reward functions. The intellectual merit lies in addressing the agent coordination problem in a physical setting by shifting the focus from ``how to learn" to ``what to learn." This paradigm shift allows a separation between the learning algorithms used by agents, and the reward functions used to tie those learning systems into system performance. By exploring agent reward functions that implicitly model agent interactions based on feedback from the real world, this work aims to build cyber-physical systems where an agent that learns to optimize its own reward leads to the optimization of the system objective function. The broader impact is in providing new air traffic flow management algorithms that will significantly reduce air traffic congestion. The potential impact cannot only be measured in currency ($41B loss in 2007) but in terms of improved experience by all travelers, providing a significant benefit to society. In addition, the PIs will use this project to train graduate and undergraduate students (i) by developing new courses in multi-agent learning for transportation systems; and (ii) by providing summer internship opportunities at NASA Ames Research Center.

The objective of this research is the development of novel control architectures and computationally efficient controller design algorithms for distributed cyber-physical systems with decentralized information infrastructures and limited communication capabilities. Active safety in Intelligent Transportation Systems will be the focus cyber-physical application. For the successful development and deployment of cooperative active safety systems, it is critical to develop theory and techniques to design algorithms with guaranteed safety properties and predictable behavior. The approach is to develop a new methodology for the design of communicating distributed hybrid controllers by integrating in a novel manner discrete-event controller design and hybrid controller design and optimization. The methodology to be developed will exploit problem decomposition and will have significant technological impact for a large class of cyber-physical systems that share features of modularity in system representation, partial information, and limited communication. The focus on distributed control strategies with limited communication among agents is addressing an important gap in existing control theories for cyber-physical systems. The approach will mitigate the computational limitations of existing approaches to control design for hybrid systems. Given the focus on cooperative active safety in Intelligent Transportation Systems, the results of this effort will have significant societal impact in terms of increased traffic safety and reduced number and severity of accidents. The broader impacts of this proposal also include involvement of high-school and undergraduate students and curriculum development by incorporating results of research into existing courses on cyber-physical systems.