Abstract
The objective of this research is to develop methods and tools for designing, implementing and verifying medical robotics. The approach is to capture the computational work-flow of systems with cyber, physical and biological components, to verify that work-flow and to synthesize systems from the work-flow model. The focusing application of this research is MRI-guided, high-frequency ultrasonic tumor ablation. MRI-guided ultrasonic tumor ablation poses challenges beyond the scope of current verification techniques. Medicine is filled with highly non-linear biological systems, which puts them at the frontier of mathematically rigorous correctness checking and verification. For instance, in this research, guaranteeing the safety of a cancer patient undergoing treatment will require verifying against Pennes bioheat equation, a non-linear differential equation with dozens of environmental factors. This research tackles such complexity using tiers of abstractions to efficiently, precisely and safely approximate the behavior of each component of a system. To ensure a faithful implementation of controllers, this research will investigate synthesizing the control code directly from the verified model in a correct by construction manner. The project will help develop the most appropriate family of formal methods for handling the safety and correctness challenges in the area of medical robotics. It directly addresses the CPS agenda of methods and tools by proposing formal techniques that bridge the gap between the cyber and physical elements. It will train manpower in cross-disciplinary areas through new seminars, workshops and courses. And, last but not least, the project will make a direct humanitarian impact on the well-being of society.
Performance Period: 09/15/2010 - 02/28/2014
Institution: University of Utah
Sponsor: National Science Foundation
Award Number: 1035658
Abstract
The objective of this research is to develop new foundations of composition in heterogeneous systems, to apply these foundations in a new generation of tools for system integration, and to validate the results in experiments using automotive and avionics System-of-Systems experimental platforms. The approach exploits simplification strategies: develop theories, methods, and tools to assist in inter-layer decoupling.
The research program has three focus areas:
(1) theory of compositionality in heterogeneous systems,
(2) tools and tool architectures for system integration, and
(3) systems/experimental research.
The project develops and deploys theories and methods for inter-layer decoupling that prevent or decrease the formation of intractable system-wide interdependences and maintain compositionality at each layer for carefully selected, essential system properties. Compositionality in tools is sought by exploring semantic foundations for model-based design. Systems/experimental research is conducted in collaboration with General Motors Global R&D (GM) and focuses on electric car platforms.
The project is contributing to the cost effective development and deployment of many safety and security-critical cyber-physical systems, ranging from medical devices to transportation, to defense and avionics. The participating institutions seek to complement the conventional curriculum in systems science with one that admits computation as a primary concept. The curriculum changes will be aggressively promoted through a process of workshops and textbook preparation.
Janos Sztipanovits
Dr. Janos Sztipanovits is currently the E. Bronson Ingram Distinguished Professor of Engineering at Vanderbilt University. He is founding director of the Institute for Software Integrated Systems (ISIS). His current research interest includes the foundation and applications of Model-Integrated Computing for the design of Cyber Physical Systems. His other research contributions include structurally adaptive systems, autonomous systems, design space exploration and systems-security co-design technology. He served as program manager and acting deputy director of DARPA/ITO between 1999 and 2002 and he was member of the US Air Force Scientific Advisory Board between 2006-2010. He was founding chair of the ACM Special Interest Group on Embedded Software (SIGBED). Dr. Sztipanovits was elected Fellow of the IEEE in 2000 and external member of the Hungarian Academy of Sciences in 2010. He graduated (Summa Cum Laude) from the Technical University of Budapest in 1970 and received his doctorate from the Hungarian Academy of Sciences in 1980.
Performance Period: 10/01/2010 - 09/30/2016
Institution: Vanderbilt University
Sponsor: National Science Foundation
Award Number: 1035655
Project URL
Project URL
Abstract
Tens of thousands of the nation?s bridges are structurally deficient. This project proposes to design a self sustaining, wireless structural monitoring system. The novel low-power Flash FPGA-based hardware platform and the corresponding software architecture offer a radically new approach to CPS design. A soft multi-core platform where software modules that run in parallel will be guaranteed to have dedicated single-threaded soft processor cores enables flexible power management by running only the necessary cores at any given time at the slowest clock rate mandated by the observed/controlled physical phenomena. As bridges tend to vibrate due to wind and dynamic load conditions, we are developing a novel vibration-based energy harvesting device that is capable of automatically adjusting its resonant response in order to capture much more energy than the current techniques can. Moreover, the PIs are developing structural health assessment techniques involving quantitative analysis of signals to determine crack type, location and size. The technology will indicate structural problems before they become critical potentially saving human lives and averting late and extensive repairs. The impact of the vibration harvesting technique and the soft multi-core architecture will go beyond structural monitoring. A separate soft core dedicated to each software component that interacts with the physical world will make CPS more responsive while saving power at the same time. The education plan focuses on outreach toward underrepresented minorities by recruiting such undergraduates to participate in the research. To facilitate the dissemination of our results, all hardware designs and software developed under this project will be open source.
Peter Volgyesi
Peter Volgyesi is a Research Scientist at the Institute for Software Integrated Systems at Vanderbilt University. In the past decade Mr. Volgyesi has been working on several novel and high impact projects sponsored by DARPA, NSF, ONR, ARL and industrial companies (Lockheed Martin, BAE Systems, the Boeing Company, Raytheon, Microsoft). He is one of the architects of the Generic Modeling Environment, a widely used metaprogrammable visual modeling tool, and WebGME - its modern web-based variant. Mr. Volgyesi had a leading role in developing the real-time signal processing algorithms in PinPtr, a low cost, low power countersniper system. He also participated in the development of the Radio Interferometric Positioning System (RIPS), a patented technology for accurate low-power node localization. As PI on two NSF funded projects Mr. Volgyesi and his team developed a low-power software-defined radio platform (MarmotE) and a component-based development toolchain targeting multicore SoC architectures for wireless cyber-physical systems. His team won the Preliminary Tournament of the DARPA Spectrum Challenge in September, 2013.
Performance Period: 10/01/2010 - 09/30/2014
Institution: Vanderbilt University
Sponsor: National Science Foundation
Award Number: 1035627
Project URL
Project URL
Abstract
The objective of this research is to develop a prototype programmable microfluidic laboratory-on-chip that concurrently executes assays (chemical algorithms) in an on-line fashion. A chemist specifies an assay (chemical algorithm) using a text-based language. Assays arrive at the device in real-time and an operating system/virtual machine running on an attached microcontroller interprets them. The approach is to develop a software simulation infrastructure for the laboratory-on-chip and to build the operating system/virtual machine on top of it. The intellectual merit of this activity is due to the fact that no type of runtime support system has yet been proposed for microfluidic devices. The key challenges to be solved in this project include: deadlock-free deterministic and adaptive routing algorithms; real-time constraints for routing droplets in the system; routing wash droplets for decontamination; scheduling assay operations on the devices; congestion estimation; and fault diagnosis and recovery. In terms of broader impact, advances in laboratory-on-chip technology will improve public health worldwide and lead to significant advances in clinical diagnostics and medicine. Laboratory-on-chips are commercially available from established companies such as Agilent Technologies as well as startup companies such as Advanced Liquid Logic, Silicon Biosystems, and Ayanda Biosystems; thus, the economic impact of this research is tremendous. The University of California, Riverside is a Minority-Serving Institution. The PI is committed to the introduction of laboratory-on-chip technology in both undergraduate and graduate education and will make every possible effort to recruit underrepresented minorities (including women) at the graduate and undergraduate level to work on the project.
Performance Period: 09/15/2010 - 08/31/2015
Institution: University of California at Riverside
Sponsor: National Science Foundation
Award Number: 1035603
Abstract
Complex surgical procedures in hospitals are increasingly aided by robotic surgery systems, often at the request of patients. These systems allow greatly increased precision, reach and flexibility to the surgeon. However, their powerful capabilities entail substantial system complexity in both hardware and software. The high probability of serious injuries should a malfunction occur calls for rigorous assessment and monitoring of the reliability and safety of these cyber-physical systems. In this research project, a framework for assessing and monitoring the reliability and safety of robotic surgery systems during development, field testing, and general deployment is being developed. The proposed framework complements existing techniques used in earlier phases of validation by taking into account how surgeons actually use a robotic surgery system, how it is affected by operating conditions, and how its observable behavior is related to its hardware and software dynamics. Before deployment, this framework uses accurate simulations to assess pre-clinical reliability. After deployment, the framework uses data collection through online monitoring of the system as it is being used in the field, followed by analysis to obtain assessments of operational reliability and safety. The collected data is also used to improve the simulations for future testing. The framework also aims to support post-market surveillance of these systems by providing a workable basis for reassessing reliability and safety properties after system maintenance. The developed tools and methods will also have applications in the validation of safety and reliability of other medical devices with embedded software and other cyber-physical systems in general.
Performance Period: 09/01/2010 - 12/31/2015
Institution: Case Western Reserve University
Sponsor: National Science Foundation
Award Number: 1035602
Abstract
The objective of this research is to develop a cyber-physical system capable of displaying the in vivo surgical area directly onto patients' skin in real-time high definition. This system will give surgeons an x-ray vision experience, since they see directly through the skin, and remove a spatial bottleneck and additional scarring caused by laparoscopes in minimally invasive surgery. The approach is to develop micro-cameras that: occupy no space required by surgical tools, produce no additional scarring to the patient, and transfer wireless high-definition video images. A virtual view generating system will project the panoramic videos from all cameras to the right spot on the patient?s body with geometry and color distortion compensation. A surgeon-camera-interaction system will be investigated to allow surgeons to control viewpoint with gesture recognition and finger tracking. Novel techniques will be developed for zero-latency high-definition wireless video transfer through the in vivo/ex vivo medium. Image viewpoint alignment and distortion compensation in real time will also be investigated. The results will be a potential paradigm shift in minimally invasive surgery. The proposed work benefits the millions of surgeries capable of being performed through a single incision in the abdomen by providing virtually transparent skin to surgeons who will enjoy all the visual benefits of open-cavity surgery without all the associated risks to the patient. The goals of this research are extremely hands-on and immediately applicable to outreach activities that can excite youth, minority students, and others about the science, medicine a and engineering careers.
Yu Sun
I am currently an Assistant Professor in the Department of Computer Science and Engineering at the University of South Florida. I was a Postdoctoral Associate at Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA from Dec. 2007 to May 2008 and a Postdoctoral Associate in the School of Computing at the University of Utah from May 2008 to May 2009. I received my B.S. and M.S. degrees in electrical engineering from Dalian University of Technology, Dalian, China, in 1997 and 2000, respectively, and Ph.D. degree in computer science from the University of Utah, Salt Lake City, in 2007.
My research interests include robotics, haptics, computer vision, human computer interaction (HCI), and medical applications.
Performance Period: 09/15/2010 - 08/31/2015
Institution: University of South Florida
Sponsor: National Science Foundation
Award Number: 1035594
Abstract
The objective of this research is to apply grammatical inference models recently developed in the field of linguistics and phonology, as a basis for abstraction, composition, symbolic control, and learning in distributed multi-agent cyber-physical systems. The approach is to map the system dynamics, specifications, and task interdependences to finite abstract models, and then describe the desired behavior of the system in an appropriate grammar that can be decomposed into local agent specifications. In this framework, the agents can learn the behavior of their environment by observing its dynamics, and update their specifications accordingly. The proposed approach to learning in cyber-physical systems, which is based on grammatical inference at a purely discrete level, is a significant departure from current works. Following this approach, one can reason about large-scale processes resulting from event interdependencies between agents, without having to construct large product systems. To realize this plan, specific technical advances on modeling, abstraction, and control synthesis are proposed. Questions related to formally factoring and composing heterogeneous systems are pervasive in the fields of formal languages and computational learning. There are also applications of commercial significance in the area of discovering new azeotropic mixtures based on documented pairs of compounds that are known to have the particular property. Proposed dissemination and outreach activities include the involvement of middle and high school students and teachers, integrated in existing NSF-sponsored programs at the University of Delaware and Boston University.
Performance Period: 09/15/2010 - 08/31/2015
Institution: Trustees of Boston University
Sponsor: National Science Foundation
Award Number: 1035588
Abstract
The objective of this research is to apply grammatical inference models recently developed in the field of linguistics and phonology, as a basis for abstraction, composition, symbolic control, and learning in distributed multi-agent cyber-physical systems. The approach is to map the system dynamics, specifications, and task interdependences to finite abstract models, and then describe the desired behavior of the system in an appropriate grammar that can be decomposed into local agent specifications. In this framework, the agents can learn the behavior of their environment by observing its dynamics, and update their specifications accordingly. The proposed approach to learning in cyber-physical systems, which is based on grammatical inference at a purely discrete level, is a significant departure from current works. Following this approach, one can reason about large-scale processes resulting from event interdependencies between agents, without having to construct large product systems. To realize this plan, specific technical advances on modeling, abstraction, and control synthesis are proposed. Questions related to formally factoring and composing heterogeneous systems are pervasive in the fields of formal languages and computational learning. There are also applications of commercial significance in the area of discovering new azeotropic mixtures based on documented pairs of compounds that are known to have the particular property. Proposed dissemination and outreach activities include the involvement of middle and high school students and teachers, integrated in existing NSF-sponsored programs at the University of Delaware and Boston University.
Performance Period: 09/15/2010 - 08/31/2015
Institution: University of Delaware
Sponsor: National Science Foundation
Award Number: 1035577
Abstract
The objective of this research is to enable cyberphysical systems (CPS) to be context-aware of people in the environment and to use data from real-world probabilistic sensors. The approach is (1) to use radio tomography (RT) and RFID to provide awareness (location and potential identification) of every person in a building or area, and (2) to develop new middleware tools to enable context-aware computing systems to use probabilistic data, thus allowing new applications to exploit sometimes unreliable estimates of the environment.The intellectual merit of the proposal is in the development of new algorithms and models for building-scale RT with low radio densities and across multiple frequencies; the development of efficient multichannel access protocols for rapid and adaptive peer-to-peer measurements; the development of space-time and probabilistic data representations for use in stream-based context awareness systems and for merging ID and non-ID data; (4) and the development of a human context-aware software development toolkit that interfaces between probabilistic data and context-aware applications.
The proposal impacts broadly the area of Cyber-physical systems that reason about human presence and rely on noisy and potentially ambiguous (practical) sensors. The research has additional dramatic impact in: (1) smart facilities which automatically enforce safety, privacy, and security procedures, increasing the ability to respond in emergency situations and prevent accidents and sabotage; (2) elder care, to monitor for physical or social decline so that effective intervention can be implemented, extending the period elders can live in their own home, without pervasive video surveillance.
Performance Period: 09/15/2010 - 08/31/2015
Institution: University of Utah
Sponsor: National Science Foundation
Award Number: 1035565
Abstract
The objective of this research is to develop an atomic force microscope based cyber-physical system that can enable automated, robust and efficient assembly of nanoscale components such as nanoparticles, carbon nanotubes, nanowires and DNAs into nanodevices. The approach in this project is based on the premise that automated, robust and efficient nanoassembly can be achieved through tip based pushing in an atomic force microscope with intermittent local scanning of nanoscale components. In particular, in order to resolve temporally and spatially continuous movement of nanoscale components under tip pushing, the research is exploring the combination of intermittent local scanning and interval non-uniform rational B-spline based isogeometric analysis in this research. Successful completion of this research is expected to lead to foundational theories and algorithmic infrastructures for effective integration of physical operations (pushing and scanning) and computation (planning and simulation) for robust, efficient and automated nanoassembly. The resulting theories and algorithms will also be applicable to a broader set of cyber physical systems. If successful, this research will lead to leap progress in nanoscale assembly, from prototype demonstration to large-scale manufacturing. Through its integrated research, education and outreach activities, this project is providing experiences and understanding in cyber-physical systems and nanoassembly for students from high schools to graduate schools. The goal is to increase interest in science and engineering among domestic students and therefore strengthen our competitiveness in the global workforce.
Performance Period: 09/15/2010 - 08/31/2013
Institution: University of Pittsburgh
Sponsor: National Science Foundation
Award Number: 1035563