The objective of this research is to develop methods and tools for a multimodal and multi-sensor assessment and rehabilitation game system called CPLAY for children with Cerebral Palsy (CP). CPLAY collects and processes multiple types of stimulation and performance data while a child is playing. Its core has a touch-screen programmable game that has various metrics to measure delay of response, score, stamina/duration, accuracy of motor/hand motion. Optional devices attached to extend CPLAY versions provide additional parallel measurements of level of concentration/participation/engagement that quantify rehabilitation activity. The approach is to model the process as a cyber-physical system (CPS) feedback loop whereby data collected from various physical 3D devices (including fNIR brain imaging) are processed into hierarchical events of low-to-high semantic meaning that impact/ adjust treatment decisions. Intellectual Merit: The project will produce groundbreaking algorithms for event identification with a multi-level data to knowledge feedback loop approach. New machine learning, computer vision, data mining, multimodal data fusion, device integration and event-driven algorithms will lead towards a new type of cyber- physical rehabilitation science for neurological disorders. It will deliver fundamental advancements to engineering by showing how to integrate physical devices with a computationally quantitative platform for motor and cognitive skills assessment. Broader Impacts: The project delivers a modular & expandable game system that has huge implications on the future of US healthcare and rehabilitation of chronic neurological disabilities. It brings hope to children with Cerebral Palsy via lower cost and remote rehabilitation alternatives. It brings new directions to human centered computing for intelligent decision-making that supplements evidence-based practices and addresses social and psychological isolation problems.

The objective of this research is to understand the loosely coupled networked control systems and to address the scientific and technological challenges that arise in their development and operation. The approach is to (1) develop a mathematical abstraction of the CPS, and an online actuation decision model that takes into account temporal and spatial dependencies among actions; (2) develop algorithms and policies to effectively manage the system and optimize its performance with respect to applications' QoS requirements; and (3) develop an agent-based event-driven framework to facilitate engineers easily monitor, (re)configure and control the system to achieve optimized results. The developed methodologies, algorithms, protocols and frameworks will be evaluated on testbeds and by our collaborating institution. The project provides fundamental understanding of loosely coupled networked control systems and a set of strategies in managing such systems. The components developed under this project enables the use of wireless-sensor-actuator networks for control systems found in a variety of disciplines and benefits waterway systems, air/ground transportation systems, power grid transmission systems, and the sort. The impact of this project is broadened through collaborations with our collaborating institution. This project provides a set of strategies and tools to help them meet the new standards. The inter-disciplinary labs and curriculum development at both undergraduate and graduate level with an emphasis on CPS interdisciplinary applications, theoretical foundations, and CPS implementations prepare our students as future workforce in the area of CPS applications.

The objective of this research is the creation of a coastal observing system that enables dense, in situ, 4D sensing through networked, sensor-equipped underwater drifters. The approach is to develop the technologies required to deploy a swarm of autonomous buoyancy controlled drifters, which are vehicles that can control their depth, but are otherwise carried entirely by the ocean currents. Such Lagrangian sampling promises to deliver a wealth of new data, ranging from applications in physical oceanography (mapping 3D currents), biology (observing the dispersion of larvae and nutrients), environmental science (tracking coastal pollutants and effluents from storm drains), and security (monitoring harbors and ports). This observing system fundamentally requires accurate positions of the drifters (to interpret the spatial correlations of data samples), swarm control algorithms (to achieve desired sampling topologies), and wireless communication (to coordinate between the individual drifters). This research will create distributed techniques to self-localize the drifter swarm, novel swarm control algorithms that enable topology manipulation while purely leveraging the stratified flow environment, and efficient wireless underwater communication for information sharing. This project has significant societal impact and educational elements. Underwater drifter swarms will enable novel insights into a wide array of scientific questions, including understanding plankton transport, accumulation and dispersion as well as monitoring harmful algal blooms. Undergraduates will play an active role in many aspects of this project, thereby offering them a uniquely interdisciplinary experience. Finally, outreach to high school students will occur through the UCSD COSMOS summer program.

The objective of this research is to develop advanced distributed monitoring and control systems for civil infrastructure. The approach uses a cyber-physical co-design of wireless sensor-actuator networks and structural monitoring and control algorithms. The unified cyber-physical system architecture and abstractions employ reusable middleware services to develop hierarchical structural monitoring and control systems. The intellectual merit of this multi-disciplinary research includes (1) a unified middleware architecture and abstractions for hierarchical sensing and control; (2) a reusable middleware service library for hierarchical structural monitoring and control; (3) customizable time synchronization and synchronized sensing routines; (4) a holistic energy management scheme that maps structural monitoring and control onto a distributed wireless sensor-actuator architecture; (5) dynamic sensor and actuator activation strategies to optimize for the requirements of monitoring, computing, and control; and (6) deployment and empirical validation of structural health monitoring and control systems on representative lab structures and in-service multi-span bridges. While the system constitutes a case study, it will enable the development of general principles that would be applicable to a broad range of engineering cyber-physical systems. This research will result in a reduction in the lifecycle costs and risks related to our civil infrastructure. The multi-disciplinary team will disseminate results throughout the international research community through open-source software and sensor board hardware. Education and outreach activities will be held in conjunction with the Asia-Pacific Summer School in Smart Structures Technology jointly hosted by the US, Japan, China, and Korea.

Abstract The objective of this research is to develop advanced distributed monitoring and control systems for civil infrastructure. The approach uses a cyber-physical co-design of wireless sensor-actuator networks and structural monitoring and control algorithms. The unified cyber-physical system architecture and abstractions employ reusable middleware services to develop hierarchical structural monitoring and control systems. The intellectual merit of this multi-disciplinary research includes (1) a unified middleware architecture and abstractions for hierarchical sensing and control; (2) a reusable middleware service library for hierarchical structural monitoring and control; (3) customizable time synchronization and synchronized sensing routines; (4) a holistic energy management scheme that maps structural monitoring and control onto a distributed wireless sensor-actuator architecture; (5) dynamic sensor and actuator activation strategies to optimize for the requirements of monitoring, computing, and control; and (6) deployment and empirical validation of structural health monitoring and control systems on representative lab structures and in-service multi-span bridges. While the system constitutes a case study, it will enable the development of general principles that would be applicable to a broad range of engineering cyber-physical systems. This research will result in a reduction in the lifecycle costs and risks related to our civil infrastructure. The multi-disciplinary team will disseminate results throughout the international research community through open-source software and sensor board hardware. Education and outreach activities will be held in conjunction with the Asia-Pacific Summer School in Smart Structures Technology jointly hosted by the US, Japan, China, and Korea.

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.

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.

The objective of this research is to develop advanced distributed monitoring and control systems for civil infrastructure. The approach uses a cyber-physical co-design of wireless sensor-actuator networks and structural monitoring and control algorithms. The unified cyber-physical system architecture and abstractions employ reusable middleware services to develop hierarchical structural monitoring and control systems. The intellectual merit of this multi-disciplinary research includes (1) a unified middleware architecture and abstractions for hierarchical sensing and control; (2) a reusable middleware service library for hierarchical structural monitoring and control; (3) customizable time synchronization and synchronized sensing routines; (4) a holistic energy management scheme that maps structural monitoring and control onto a distributed wireless sensor-actuator architecture; (5) dynamic sensor and actuator activation strategies to optimize for the requirements of monitoring, computing, and control; and (6) deployment and empirical validation of structural health monitoring and control systems on representative lab structures and in-service multi-span bridges. While the system constitutes a case study, it will enable the development of general principles that would be applicable to a broad range of engineering cyber-physical systems. This research will result in a reduction in the lifecycle costs and risks related to our civil infrastructure. The multi-disciplinary team will disseminate results throughout the international research community through open-source software and sensor board hardware. Education and outreach activities will be held in conjunction with the Asia-Pacific Summer School in Smart Structures Technology jointly hosted by the US, Japan, China, and Korea.

The objective of this research is the creation of a coastal observing system that enables dense, in situ, 4D sensing through networked, sensor-equipped underwater drifters. The approach is to develop the technologies required to deploy a swarm of autonomous buoyancy controlled drifters, which are vehicles that can control their depth, but are otherwise carried entirely by the ocean currents. Such Lagrangian sampling promises to deliver a wealth of new data, ranging from applications in physical oceanography (mapping 3D currents), biology (observing the dispersion of larvae and nutrients), environmental science (tracking coastal pollutants and effluents from storm drains), and security (monitoring harbors and ports). This observing system fundamentally requires accurate positions of the drifters (to interpret the spatial correlations of data samples), swarm control algorithms (to achieve desired sampling topologies), and wireless communication (to coordinate between the individual drifters). This research will create distributed techniques to self-localize the drifter swarm, novel swarm control algorithms that enable topology manipulation while purely leveraging the stratified flow environment, and efficient wireless underwater communication for information sharing. This project has significant societal impact and educational elements. Underwater drifter swarms will enable novel insights into a wide array of scientific questions, including understanding plankton transport, accumulation and dispersion as well as monitoring harmful algal blooms. Undergraduates will play an active role in many aspects of this project, thereby offering them a uniquely interdisciplinary experience. Finally, outreach to high school students will occur through the UCSD COSMOS summer program.

The objective of this research is to study such properties of classes of cooperative multi-agent systems as stability, performance, and robustness. Multi-agent systems such as vehicle platoons and coupled oscillators can display emergent behavior that is difficult to predict from the behavior of individual subsystems. The approach is to develop and extend the theory of fundamental design limitations to cover multi-agent systems that communicate over both physical and virtual communication links. The theory will further describe known phenomena, such as string instability, and extend the analysis to other systems, such as harmonic oscillators. The theory will be tested and validated in the Michigan Embedded Control Systems Laboratory. The intellectual merit of the proposed research will be the development of tools that delineate tradeoffs between performance and feedback properties for control systems involving mixes of human and computer agents and classes of hardware dynamics, controllers, and network topology. The contribution to system behavior of each agent's realization in hardware (constrained by Newton's laws) and realization in software and communications (subject to the constraints discovered by Shannon and Bode) will be assessed. The broader impacts of the proposed research will be a significant impact on teaching, both at the University of Michigan and at ETH Zurich. At each school, popular teaching laboratories allow over 100 students per year, from diverse backgrounds, to learn concepts from the field of embedded networked distributed control systems. New families of haptic devices will enable the research to be transferred into these teaching laboratories.