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.

This project develops a framework for design automation of cyber-physical systems to augment human interaction with complex systems that integrate across computational and physical environments. As a design driver, the project develops a Body/Brain Computer Interface (BBCI) for the population of functionally locked-in individuals, who are unable to interact with the physical world through movement and speech. The BBCI will enable communication with other humans through expressive language generation and interaction with the environment through robotic manipulators. Utilizing advances in system-level design, this project develops a holistic framework for design and implementation of heterogeneous human-in-the-loop cyber-physical systems composed of physically distributed, networked components. It will advance BBCI technology by incorporating context aware inference and learning of task-specific human intent estimation in applications involving semi-autonomous robotic actuators and an efficient wireless communication framework. The results of this project are expected to significantly speed up the design of complex cyber-physical systems. By accelerating the path from idea to prototype, this work shortens the time frame of and cost of development for assistive technology to improve the quality-of-life for functionally locked-in individuals. This project establishes an open prototyping platform and a design framework for rapid exploration of other novel human-in-the-loop applications. The open platform will foster undergraduate involvement in cyber-physical systems research, building confidence and expertise. In addition, new activities at the Museum of Science in Boston will engage visitors to experiment with systematic design principles in context of a brain computer interface application, while offering learning opportunities about basic brain functions.

This project develops a framework for design automation of cyber-physical systems to augment human interaction with complex systems that integrate across computational and physical environments. As a design driver, the project develops a Body/Brain Computer Interface (BBCI) for the population of functionally locked-in individuals, who are unable to interact with the physical world through movement and speech. The BBCI will enable communication with other humans through expressive language generation and interaction with the environment through robotic manipulators. Utilizing advances in system-level design, this project develops a holistic framework for design and implementation of heterogeneous human-in-the-loop cyber-physical systems composed of physically distributed, networked components. It will advance BBCI technology by incorporating context aware inference and learning of task-specific human intent estimation in applications involving semi-autonomous robotic actuators and an efficient wireless communication framework. The results of this project are expected to significantly speed up the design of complex cyber-physical systems. By accelerating the path from idea to prototype, this work shortens the time frame of and cost of development for assistive technology to improve the quality-of-life for functionally locked-in individuals. This project establishes an open prototyping platform and a design framework for rapid exploration of other novel human-in-the-loop applications. The open platform will foster undergraduate involvement in cyber-physical systems research, building confidence and expertise. In addition, new activities at the Museum of Science in Boston will engage visitors to experiment with systematic design principles in context of a brain computer interface application, while offering learning opportunities about basic brain functions.

This project takes the paradigm of cloud computing developed in the cyber-world and puts it into the physical world, to create a cyber-physical computing cloud, SAM-C. Unlike conventional cloud computing, SAM-C servers move in space, meaning, they are vehicles with physical constraints. The server vehicles also have sensors and actuators to create a way to re-organize mobile sensor networks in the paradigm of cloud computing. The project envisions an industry offering sensing as a service provided by the cloud. To enable this new service, the project extends the virtual machine instance fundamental to cloud computing with one new property -- virtual speed. The research terms this augmented entity a virtual vehicle and develops the theories, algorithms and protocols to realize many virtual vehicles over a network of real vehicle servers at scale. This research impacts the cloud computing industry by providing tools and theories it can use to leverage the many possible mobile server hosts in our society, e.g., cars, planes, people, and emerging vehicles like Unmanned Air Vehicles or drifters. It impacts mobile sensor networks by shifting them from an artifact built for an application to a service provided by a cloud. The inter-disciplinary research team spanning computer science, civil, and mechanical engineering impacts graduate and undergraduate teaching in systems, computer science, and control theory. The project guides K-12 students to build simple electric airplanes with sensors for greenhouse gas measurement thereby introducing young users of computation to cyber-physical cloud computing.

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.

This project aims to develop a computational framework and a physical platform for enabling dense networks of micro-robotic swarms for medical applications. The approach relies on a new stochastic framework for design and analysis of dense networks, as well as new fabrication and characterization methods for building and understanding bacteria propelled micro-robotic swarms. This project enhances the CPS science beyond passive networks of millimeter-scale bio-implantable devices with active networks of micro-robotic swarms that could be more effective in combating various critical diseases with minimal impact on the human body. Three major research objectives are proposed in this project: 1) Statistical physics inspired approach to the modeling and analysis of dense networks of swarms: The theory envisioned for characterizing the dynamics of dense networks of swarms aims at achieving ?beyond Turing? computation via dense networks, designing autonomous reliable communication protocols for dense networks, and estimating and controlling their performance; 2) Fabrication and steering of swarms of bacteria propelled swimming micro-robots: Large numbers of both chemotactic and magnetotactic bacteria integrated micro-robotic bodies will be fabricated using self-assembly and micro/nano-fabrication methods. Chemotaxis and magnetotaxis will be respectively used as passive and active steering mechanisms for navigating the swarms of micro-robots in small spaces to perform specified tasks; 3) Characterization of the behavior and control of bacteria propelled micro-robotic swarms: To validate and fine tune the proposed computational models, the motion and behavior of single and large numbers of bacteria propelled micro-robots will be characterized using optical and other microscopy methods. Intellectual Merit: The research breakthrough proposed herein consists of building a new physical platform for micro-robotic swarms by using attached bacteria as on-board actuators and chemotaxis and magnetotaxis as passive and active steering control methods, and developing a new computational dense network framework for designing and analyzing such stochastic micro-robotic swarms. The statistical computational framework to be developed in this study will improve understanding of swarming behavior and control of large numbers of bacteria propelled micro-robots. This framework offers an integrated approach towards CPS design that is meant to operate under uncertainty conditions, yet be able to succeed in performing a specified task through self-organization and collective behavior. This bottom-top approach is meant to improve the theoretical foundations of the current computational models of CPS. Broader Impacts: The resulting computational framework and the physical platform could be adapted to a wide range of different stochastic dense network systems ranging from migration of cancer cell populations or dynamics of virus populations to immune system support and modeling. The proposed swarms of bacteria integrated micro-robots have potential future applications in health-care for the diagnosis of diseases and targeted drug delivery inside the stagnant or low velocity fluids of the human body or the medical diagnosis inside lab-on-a-chip microfluidic devices. Such health-care applications could improve the welfare of our society. To foster learning and training of next generation CPS workforce, the PIs plan to emphasize a cross-disciplinary approach to teaching topics that are usually offered in disjoint tracks. The PIs will integrate the CPS research activities in this study into their newly developed courses, and they will also teach one of these courses jointly. As a joint international educational activity, a three-day Summer School will be held alternately in US and Europe every year on various CPS topics related to our project. This will help building a strong international CPS community and training US and European students in CPS topics. The PIs will present the research results of this project to children, K-12 students, K-12 teachers, IEEE and ACM student members, and college students inside and outside of USA through public lectures. This project and the Sloan Foundation will support underrepresented and minority graduate students in the project. Moreover, underrepresented minority undergraduate students will be trained through the CMU ICES summer outreach program called The SURE Thing and the NSF REU program.