Advances in technology mean that computer-controlled physical devices that currently still require human operators, such as automobiles, trains, airplanes, and medical treatment systems, could operate entirely autonomously and make rational decisions on their own. Autonomous cars and drones are a concrete and highly publicized face of this dream. Before this dream can be realized we must address the need for safety - the guaranteed absence of undesirable behaviors emerging from autonomy. Highly publicized technology accidents such as rocket launch failures, uncontrolled exposure to radiation during treatment, aircraft automation failures and unintended automotive accelerations serve as warnings of what can happen if safety is not adequately addressed in the design of such cyber-physical systems. One approach for safety analysis is the use of software tools that apply formal logic to prove the absence of undesired behavior in the control software of a system. In prior work, this approach this been proven to work for simple controller software that is generated automatically by tools from abstract models like Simulink diagrams. However, autonomous decision making requires more complex software that is able to solve optimization problems in real time. Formal verification of control software that includes such optimization algorithms remains an unmet challenge. The project SORTIES (Semantics of Optimization for Real Time Intelligent Embedded Systems) draws upon expertise in optimization theory, control theory, and computer science to address this challenge. Beginning with the convergence properties of convex optimization algorithms, SORTIES examines how these properties can be automatically expressed as inductive invariants for the software implementation of the algorithms, and then incorporates these properties inside the source code itself as formal annotations which convey the underlying reasoning to the software engineer and to existing computer-aided verification tools. The SORTIES goal is an open-source-semantics-carrying autocoder, which takes an optimization algorithm and its convergence properties as input, and produces annotated, verifiable code as output. The demonstration of the tool on several examples, such as a Mars lander, an aircraft avionics system, and a jet engine controller, shows that the evidence of quality produced by annotations is fully compatible with its application to truly functional products. Project research is integrated with education through training of "tri-lingual" professionals, who are equally conversant in system operation, program analysis, and the theory of control and optimization.

The project focuses on swarming cyber-physical systems (swarming CPS) consisting of a collection of mobile networked agents, each of which has sensing, computing, communication, and locomotion capabilities, and that have a wide range of civilian and military applications. Different from conventional static CPS, swarming CPS rely on mobile computing entities, e.g., robots, which collaboratively interact with phenomena of interest at different physical locations. This unique feature calls for novel sensing-motion co-design solutions to accomplish a variety of increasingly complex missions. Towards this, the overall research objective of this project is to establish and demonstrate a generic motion-sensing co-design procedure that will significantly reduce the complexity of the mission design for swarming CPS, and greatly facilitate the development of effective, efficient and adaptive control and sensing strategies under various environment uncertainties. This project aims to offer comprehensive scientific understanding of the dynamic nature of swarming CPS, contribute to generic engineering principles for designing collaborative control and sensing algorithms, and advance the enabling technologies of practically applying CPS in the challenging environment. The research solutions of this project aim to bring significant advance in the environmental sustainability, homeland security, and human well-being. The project provides unique interdisciplinary training opportunities for graduate and undergraduate students through both research work and related courses that the PIs will develop and offer. The project significantly advances the state of the art in cooperative control and sensing and provide an enabling technology for swarming CPS through highly interrelated thrusts: (1) a generic sensing and motion co-design procedure, which reveals the fundamental interplay between the sensing dynamics and motion dynamics of swarming CPS, will be proposed to facilitate the development of effective and efficient control and sensing strategies; (2) by following such co-design procedure, provable correct, computation efficient, and communication light control and sensing strategies will be developed for swarming CPS with constrained resources to accomplish specific missions, e.g., locating pollutants, in an unknown field, while navigating through uncertain spaces; (3) to provide an enabling mobile platform to verify the proposed strategies, innovative small, highly 3D maneuverable, noiseless, energy-efficient, and robust robotic fish fully actuated by smart material will be designed to meet the maneuvering requirements of the proposed algorithms; (4) novel Magnetic Induction (MI)-based underwater communication and localization solutions will be developed, which allows robotic fish to timely and reliably exchange messages, while simultaneously providing accurate inter-fish localization in the harsh 3D underwater environment; and (5) the proposed sensing-motion co-design strategies will be verified and demonstrated using a school of wirelessly interconnected robotic fish in both lab-based experiments and field experiments.

Recent developments in nanotechnology and synthetic biology have enabled a new direction in biological engineering: synthesis of collective behaviors and spatio-temporal patterns in multi-cellular bacterial and mammalian systems. This will have a dramatic impact in such areas as amorphous computing, nano-fabrication, and, in particular, tissue engineering, where patterns can be used to differentiate stem cells into tissues and organs. While recent technologies such as tissue- and organoid on-a-chip have the potential to produce a paradigm shift in tissue engineering and drug development, the synthesis of user-specified, emergent behaviors in cell populations is a key step to unlock this potential and remains a challenging, unsolved problem. This project brings together synthetic biology and micron-scale mobile robotics to define the basis of a next-generation cyber-physical system (CPS) called biological CPS (bioCPS). Synthetic gene circuits for decision making and local communication among the cells are automatically synthesized using a Bio-Design Automation (BDA) workflow. A Robot Assistant for Communication, Sensing, and Control in Cellular Networks (RA), which is designed and built as part of this project, is used to generate desired patterns in networks of engineered cells. In RA, the engineered cells interact with a set of micro-robots that implement control, sensing, and long-range communication strategies needed to achieve the desired global behavior. The micro-robots include both living and non-living matter (engineered cells attached to inorganic substrates that can be controlled using externally applied fields). This technology is applied to test the formation of various patterns in living cells. The project has a rich education and outreach plan, which includes nationwide activities for CPS education of high-school students, lab tours and competitions for high-school and undergraduate students, workshops, seminars, and courses for graduate students, as well as specific initiatives for under-represented groups. Central to the project is the development of theory and computational tools that will significantly advance that state of the art in CPS at large. A novel, formal methods approach is proposed for synthesis of emergent, global behaviors in large collections of locally interacting agents. In particular, a new logic whose formulas can be efficiently learned from quad-tree representations of partitioned images is developed. The quantitative semantics of the logic maps the synthesis of local control and communication protocols to an optimization problem. The project contributes to the nascent area of temporal logic inference by developing a machine learning method to learn temporal logic classifiers from large amounts of data. Novel abstraction and verification techniques for stochastic dynamical systems are defined and used to verify the correctness of the gene circuits in the BDA workflow.

The project focuses on swarming cyber-physical systems (swarming CPS) consisting of a collection of mobile networked agents, each of which has sensing, computing, communication, and locomotion capabilities, and that have a wide range of civilian and military applications. Different from conventional static CPS, swarming CPS rely on mobile computing entities, e.g., robots, which collaboratively interact with phenomena of interest at different physical locations. This unique feature calls for novel sensing-motion co-design solutions to accomplish a variety of increasingly complex missions. Towards this, the overall research objective of this project is to establish and demonstrate a generic motion-sensing co-design procedure that will significantly reduce the complexity of the mission design for swarming CPS, and greatly facilitate the development of effective, efficient and adaptive control and sensing strategies under various environment uncertainties. This project aims to offer comprehensive scientific understanding of the dynamic nature of swarming CPS, contribute to generic engineering principles for designing collaborative control and sensing algorithms, and advance the enabling technologies of practically applying CPS in the challenging environment. The research solutions of this project aim to bring significant advance in the environmental sustainability, homeland security, and human well-being. The project provides unique interdisciplinary training opportunities for graduate and undergraduate students through both research work and related courses that the PIs will develop and offer. The project significantly advances the state of the art in cooperative control and sensing and provide an enabling technology for swarming CPS through highly interrelated thrusts: (1) a generic sensing and motion co-design procedure, which reveals the fundamental interplay between the sensing dynamics and motion dynamics of swarming CPS, will be proposed to facilitate the development of effective and efficient control and sensing strategies; (2) by following such co-design procedure, provable correct, computation efficient, and communication light control and sensing strategies will be developed for swarming CPS with constrained resources to accomplish specific missions, e.g., locating pollutants, in an unknown field, while navigating through uncertain spaces; (3) to provide an enabling mobile platform to verify the proposed strategies, innovative small, highly 3D maneuverable, noiseless, energy-efficient, and robust robotic fish fully actuated by smart material will be designed to meet the maneuvering requirements of the proposed algorithms; (4) novel Magnetic Induction (MI)-based underwater communication and localization solutions will be developed, which allows robotic fish to timely and reliably exchange messages, while simultaneously providing accurate inter-fish localization in the harsh 3D underwater environment; and (5) the proposed sensing-motion co-design strategies will be verified and demonstrated using a school of wirelessly interconnected robotic fish in both lab-based experiments and field experiments.

In the next few decades, autonomous vehicles will become an integral part of the traffic flow on highways. However, they will constitute only a small fraction of all vehicles on the road. This research develops technologies to employ autonomous vehicles already in the stream to improve traffic flow of human-controlled vehicles. The goal is to mitigate undesirable jamming, traffic waves, and to ultimately reduce the fuel consumption. Contemporary control of traffic flow, such as ramp metering and variable speed limits, is largely limited to local and highly aggregate approaches. This research represents a step towards global control of traffic using a few autonomous vehicles, and it provides the mathematical, computational, and engineering structure to address and employ these new connections. Even if autonomous vehicles can provide only a small percentage reduction in fuel consumption, this will have a tremendous economic and environmental impact due to the heavy dependence of the transportation system on non-renewable fuels. The project is highly collaborative and interdisciplinary, involving personnel from different disciplines in engineering and mathematics. It includes the training of PhD students and a postdoctoral researcher, and outreach activities to disseminate traffic research to the broader public. This project develops new models, computational methods, software tools, and engineering solutions to employ autonomous vehicles to detect and mitigate traffic events that adversely affect fuel consumption and congestion. The approach is to combine the data measured by autonomous vehicles in the traffic flow, as well as other traffic data, with appropriate macroscopic traffic models to detect and predict congestion trends and events. Based on this information, the loop is closed by carefully following prescribed velocity controllers that are demonstrated to reduce congestion. These controllers require detection and response times that are beyond the limit of a human's ability. The choice of the best control strategy is determined via optimization approaches applied to the multiscale traffic model and suitable fuel consumption estimation. The communication between the autonomous vehicles, combined with the computational and control tasks on each individual vehicle, require a cyber-physical approach to the problem. This research considers new types of traffic models (micro-macro models, network approaches for higher-order models), new control algorithms for traffic flow regulation, and new sensing and control paradigms that are enabled by a small number of controllable systems available in a flow.

This project represents a cross-disciplinary collaborative research effort on developing rigorous, closed-loop approaches for designing, simulating, and verifying medical devices. The work will open fundamental new approaches for radically accelerating the pace of medical device innovation, especially in the sphere of cardiac-device design. Specific attention will be devoted to developing advanced formal methods-based approaches for analyzing controller designs for safety and effectiveness; and devising methods for expediting regulatory and other third-party reviews of device designs. The project team includes members with research backgrounds in computer science, electrical engineering, biophysics, and cardiology; the PIs will use a coordinated approach that balances theoretical, experimental and practical concerns to yield results that are intended to transform the practice of device design while also facilitating the translation of new cardiac therapies into practice. The proposed effort will lead to significant advances in the state of the art for system verification and cardiac therapies based on the use of formal methods and closed-loop control and verification. The animating vision for the work is to enable the development of a true in silico design methodology for medical devices that can be used to speed the development of new devices and to provide greater assurance that their behaviors match designers' intentions, and to pass regulatory muster more quickly so that they can be used on patients needing their care. The scientific work being proposed will serve this vision by providing mathematically robust techniques for analyzing and verifying the behavior of medical devices, for modeling and simulating heart dynamics, and for conducting closed-loop verification of proposed therapeutic approaches. The acceleration in medical device innovation achievable as a result of the proposed research will also have long-term and sustained societal benefits, as better diagnostic and therapeutic technologies enter into the practice of medicine more quickly. It will also yield a collection of tools and techniques that will be applicable in the design of other types of devices. Finally, it will contribute to the development of human resources and the further inclusion of under-represented groups via its extensive education and outreach programs, including intensive workshop experiences for undergraduates

This project represents a cross-disciplinary collaborative research effort on developing rigorous, closed-loop approaches for designing, simulating, and verifying medical devices. The work will open fundamental new approaches for radically accelerating the pace of medical device innovation, especially in the sphere of cardiac-device design. Specific attention will be devoted to developing advanced formal methods-based approaches for analyzing controller designs for safety and effectiveness; and devising methods for expediting regulatory and other third-party reviews of device designs. The project team includes members with research backgrounds in computer science, electrical engineering, biophysics, and cardiology; the PIs will use a coordinated approach that balances theoretical, experimental and practical concerns to yield results that are intended to transform the practice of device design while also facilitating the translation of new cardiac therapies into practice. The proposed effort will lead to significant advances in the state of the art for system verification and cardiac therapies based on the use of formal methods and closed-loop control and verification. The animating vision for the work is to enable the development of a true in silico design methodology for medical devices that can be used to speed the development of new devices and to provide greater assurance that their behaviors match designers' intentions, and to pass regulatory muster more quickly so that they can be used on patients needing their care. The scientific work being proposed will serve this vision by providing mathematically robust techniques for analyzing and verifying the behavior of medical devices, for modeling and simulating heart dynamics, and for conducting closed-loop verification of proposed therapeutic approaches. The acceleration in medical device innovation achievable as a result of the proposed research will also have long-term and sustained societal benefits, as better diagnostic and therapeutic technologies enter into the practice of medicine more quickly. It will also yield a collection of tools and techniques that will be applicable in the design of other types of devices. Finally, it will contribute to the development of human resources and the further inclusion of under-represented groups via its extensive education and outreach programs, including intensive workshop experiences for undergraduates.

Title: CPS: Breakthrough: Development of Novel Architectures for Control and Diagnosis of Safety-Critical Complex Cyber-Physical Systems This project is developing novel architectures for control and diagnosis of complex cyber-physical systems subject to stringent performance requirements in terms of safety, resilience, and adaptivity. These ever-increasing demands necessitate the use of formal model-based approaches to synthesize provably-correct feedback controllers. The intellectual merit of this research lies in a novel combination of techniques from the fields of dynamical systems, discrete event systems, reactive synthesis, and graph theory, together with new advancements in terms of abstraction techniques, computationally efficient synthesis of control and diagnosis strategies that support distributed implementations, and synthesis of acquisition of information and communication strategies. The project's broader significance and importance are demonstrated by the expected improvement of the safety, resilience, and performance of complex cyber-physical systems in critical infrastructures as well as the efficiency with which they are designed and certified. The original approach being developed is based on the combination of multi-resolution abstraction graphs for building discrete models of the underlying cyber-physical system with reactive synthesis techniques that exploit a representation of the solution space in terms of a finite structure called a decentralized bipartite transition system. The concepts of abstraction graph and decentralized bipartite transition system are novel and open new avenues of investigation with significant potential to the formal synthesis of safe, resilient, and adaptive controllers. This methodology naturally results in a set of decentralized and asynchronous controllers and diagnosers, which ensures greater resilience and adaptivity. Overall, this research will significantly impact the Science of Cyber-Physical Systems and the Engineering of Cyber-Physical Systems.

Driven by both civilian and military applications, such as coordinated surveillance, search and rescue, underwater or space exploration, manipulation in hazardous environments, and rapid emergency response, cooperative actions by teams of robots has emerged as an important research area. However, the coordination strategies for such robot teams are still developed to a great extent by trial-and-error processes. Hence, the strategies cannot guarantee mission success. This award supports fundamental research to provide a provably correct formal design theory of multi-robot systems that guarantees mission success. Furthermore, results from the research can be extended to the design of more general cyber-physical systems (CPSs) consisting of distributed and coordinated subsystems, such as the national power grid, ground/air traffic networks, and manufacturing systems. These CPSs are critical components of the national civil infrastructure that must operate reliably to ensure public safety. The multidisciplinary approach taken will help broaden participation of underrepresented groups in research and positively impact engineering education. Focusing on multi-robot teams, the goal of the research is to build foundations for a provably correct formal design theory for CPSs. This design theory will guarantee a given global performance of multi-robot teams through designing local coordination rules and control laws. The basic idea is to decompose the team mission into individual subtasks such that the design can be reduced to a local synthesis problem for individual robots. Multidisciplinary approaches combining hybrid systems, supervisory control, regular inference and model checking will be utilized to achieve this goal. The developed theory will enable robots in the team to cooperatively learn their individual roles in a mission, and then automatically synthesize local supervisors to fulfill their subtasks. A salient feature of this method lies on its ability to handle environmental uncertainties and unmodeled dynamics, as there is no need for an explicit model of the transition dynamics of each agent/robot and their interactions with the environment. In addition, the design is online and reactive, enabling the robot team to adapt to changing environments and dynamic tasking. The derived theory will be implemented as software tools and will be demonstrated through real robotic systems consisting of unmanned ground and aerial vehicles in unstructured urban/rural areas.

Driven by both civilian and military applications, such as coordinated surveillance, search and rescue, underwater or space exploration, manipulation in hazardous environments, and rapid emergency response, cooperative actions by teams of robots has emerged as an important research area. However, the coordination strategies for such robot teams are still developed to a great extent by trial-and-error processes. Hence, the strategies cannot guarantee mission success. This award supports fundamental research to provide a provably correct formal design theory of multi-robot systems that guarantees mission success. Furthermore, results from the research can be extended to the design of more general cyber-physical systems (CPSs) consisting of distributed and coordinated subsystems, such as the national power grid, ground/air traffic networks, and manufacturing systems. These CPSs are critical components of the national civil infrastructure that must operate reliably to ensure public safety. The multidisciplinary approach taken will help broaden participation of underrepresented groups in research and positively impact engineering education. Focusing on multi-robot teams, the goal of the research is to build foundations for a provably correct formal design theory for CPSs. This design theory will guarantee a given global performance of multi-robot teams through designing local coordination rules and control laws. The basic idea is to decompose the team mission into individual subtasks such that the design can be reduced to a local synthesis problem for individual robots. Multidisciplinary approaches combining hybrid systems, supervisory control, regular inference and model checking will be utilized to achieve this goal. The developed theory will enable robots in the team to cooperatively learn their individual roles in a mission, and then automatically synthesize local supervisors to fulfill their subtasks. A salient feature of this method lies on its ability to handle environmental uncertainties and unmodeled dynamics, as there is no need for an explicit model of the transition dynamics of each agent/robot and their interactions with the environment. In addition, the design is online and reactive, enabling the robot team to adapt to changing environments and dynamic tasking. The derived theory will be implemented as software tools and will be demonstrated through real robotic systems consisting of unmanned ground and aerial vehicles in unstructured urban/rural areas.