The objective of this research is to create interfaces that enable people with impaired sensory-motor function to control interactive cyber-physical systems such as artificial limbs, wheelchairs, automobiles, and aircraft. The approach is based on the premise that performance can be significantly enhanced merely by warping the perceptual feedback provided to the human user. A systematic way to design this feedback will be developed by addressing a number of underlying mathematical and computational challenges. The intellectual merit lies in the way that perceptual feedback is constructed. Local performance criteria like stability and collision avoidance are encoded by potential functions, and gradients of these functions are used to warp the display. Global performance criteria like optimal navigation are encoded by conditional probabilities on a language of motion primitives, and metric embeddings of these probabilities are used to warp the display. Together, these two types of feedback facilitate improved safety and performance while still allowing the user to retain full control over the system. If successful, this research could improve the lives of people suffering from debilitating physical conditions such as amputation or stroke and also could protect people like drivers or pilots that are impaired by transient conditions such as fatigue, boredom, or substance abuse. Undergraduate and graduate engineering students will benefit through involvement in research projects, and K-12 students and teachers will benefit through participation in exhibits presented at the Engineering Open House, an event hosted annually by the College of Engineering at the University of Illinois.

The objective of this research is to develop new principles for creating and comparing models of skilled human activities, and to apply those models to systems for teaching, training and assistance of humans performing these activities. The models investigated will include both hybrid systems and language-based models. The research will focus on modeling surgical manipulations during robotic minimally invasive surgery. Models for expert performance of surgical tasks will be derived from recorded motion and video data. Student data will be compared with these expert models, and both physical guidance and information display methods will be developed to provide feedback to the student based on the expert model. The intellectual merit of this work lies in the development of a new set of mathematical tools for modeling human skilled activity. These tools will provide new insights into the relationship between skill, style, and content in human motion. Additional intellectual merit lies in the connection of hybrid systems modeling to language models, the creation of techniques for automated training, and in the assessment of new training methods. The broader impact of this research will be the creation of automated methods for modeling and teaching skilled human motion. These methods will have enormous implications for the training and re-training of the US workforce. This project will also impact many diversity and outreach activities, including REU programs and summer camps for K-12 outreach. The senior personnel of this project also participate in the Robotic Systems Challenge and the Women in Science and Engineering program.

The objective of this research is to enable improved performance and application development efficiency for streaming applications. The approach is to use architecturally diverse computing engines, such as field programmable gate arrays and graphics processing units, to execute portions of an application. This approach is especially well suited to applications that process streaming data, such as from a sensor array like a telescope or other scientific instrument. Intellectual merit. While the use of architecturally diverse systems has a long history in the world of performance-critical systems that interact with the physical world, application development has always been a challenge. This proposal seeks to improve application development by making significant progress in two essential areas: performance monitors and debuggers. The approach has the following properties: it is non-intrusive with respect to the application being monitored and it supports data collection concerning rare events. In particular, it allows correlation of the cyber portion of an application with the physical portion in which the rare events occur. Broader impacts. Impact on society: The research can have a dramatic impact on cyber-physical computing applications, from scientific instrumentation to medical imaging. Improvements in power efficiency, weight, and volume are all achievable through the use of architectural diversity. Education: The proposed research will be carried out by graduate and undergraduate students, both furthering their education and increasing the nation's trained workforce. Underrepresented groups: Washington University's Chancellor's Fellowship and Olin Fellowship programs will be leveraged to attract the participation of individuals from underrepresented groups.

The objective of this research is to develop new scientific and engineering principles, algorithms and models for the design of battery powered cyber-physical systems whose computational substrates include high-performance multiprocessor systems-on-chip. The approach is to design control tasks that guarantee performance and meet criteria for battery operation time. Task schedulers are co-designed to balance the computing load across the multiple processors, and to control the physical plant together with the control tasks. The controller and scheduler will be integrated with battery management algorithms through a systems theory approach so that the methods are provably correct with justfiable performance. Intellectual Merit: The program will create progress in digital and hybrid control theory that keeps up with the recent trend of using multiprocessor systems-on-chips for control and robotic applications. The mechanism for the migration of control tasks between multiple processors will respect physical and thermal performance. A novel battery dynamic discharge model is developed, which may be applied to context when the discharge current of batteries cannot be predicted by existing static battery models. Broader Impacts: Collaborations with industrial partners have been set up. The program offers multidisciplinary training in cyber-physical systems. A teaching and outreach lab is in place to host K-12 student teams that participate in robot competitions, and has become an Explorer Post for Boy Scout of America.

The objective of this research is to develop technologies to improve the efficiency and safety of the road transportation infrastructure. The approach is to develop location-based vehicular services combining on-board automotive computers, in-car devices, mobile phones, and roadside monitoring/surveillance systems. The resulting vehicular Cyber Physical Systems (CPS) can reduce travel times with smart routing, save fuel and reduce carbon emissions by determining greener routes and commute times, improve safety by detecting road hazards, change driving behavior using smart tolling, and enable measurement-based insurance plans that incentivize good driving. This research develops distributed algorithms for predictive travel delay modeling, feedback-based routing, and road hazard assessment. It develops privacy-preserving protocols for capturing and analyzing data and using it for tasks such as congestion-aware tolling. It also develops a secure macro-tasking software run-time substrate to ensure that algorithms can be programmed centrally without explicitly programming each node separately, while ensuring that it is safe to run third-party code. The research focuses on re-usable methods that can benefit multiple vehicular services, and investigates which lessons learned from this vehicular CPS effort generalize to other situations. Road transportation is a grand challenge problem for modern society, which this research can help overcome. Automobile vendors, component developers, and municipal authorities have all shown interest in deployment. The education plan includes outreach to local K-12 students and a new undergraduate course on transportation from a CPS perspective, which will involve term projects using the data collected in the project

The physical environment of a cyber-physical system is unboundedly complex, changing continuously in time and space. An embodied cyber-physical system, embedded in the physical world, will receive a high bandwidth stream of sensory information, and may have multiple effectors with continuous control signals. In addition to dynamic change in the world, the properties of the cyber-physical system itself ? its sensors and effectors ? change over time. How can it cope with this complexity? The hypothesis behind this proposal is that a successful cyber-physical system will need to be a learning agent, learning the properties of its sensors, effectors, and environment from its own experience, and adapting over time. Inspired by human developmental learning, the assertion is that foundational concepts such as Space, Object, Action, etc., are essential for such a learning agent to abstract and control the complexity of its world. To bridge the gap between continuous interaction with the physical environment, and discrete symbolic descriptions that support effective planning, the agent will need multiple representations for these foundational domains, linked by abstraction relations. To achieve this, the team is developing the Object Semantic Hierarchy (OSH), which shows how a learning agent can create a hierarchy of representations for objects it interacts with. The OSH shows how the ?object abstraction? factors the uncertainty in the sensor stream into object models and object trajectories. These object models then support the creation of action models, abstracting from low-level motor signals. To ensure generality across cyber-physical systems, these methods make only very generic assumptions about the nature of the sensors, effectors, and environment. However, to provide a physical test bed for rapid evaluation and refinement of our methods, the team has designed a model laboratory robotic system to be built from off-the-shelf components, including a stereo camera, a pan-tilt-translate base, and a manipulator arm. For dissemination and replication of research results, the core system will be affordable and easily duplicated at other labs. There are plans to distribute the plans, the control software, and the software for experiments, to encourage other labs to replicate and extend the work. The same system will serve as a platform for an open-ended set of undergraduate laboratory tasks, ranging from classroom exercises, to term projects, to independent study projects. There is a preliminary design for a very inexpensive version of the model cyberphysical system that can be constructed from servo motors and pan-tilt webcams, for use in collaborating high schools and middle schools, to communicate the breadth and excitement of STEM research.

The objective of this research is to enable operation of synthetic and cyborg insects in complicated environments, such as outdoors or in a collapsed building. As the mobile platforms and environment have significant uncertainty, learning and adaptation capabilities are critical. The approach consists of three main thrusts to enable the desired learning and adaptation: (i) Development of algorithms to efficiently learn optimal control policies and dynamics models through sharing the learning and adaptation between various instantiations of platforms and environments. (ii) Creation of control learning algorithms which can be run on low-cost, low-power mobile platforms. (iii) Development of algorithms for online improvement of policy performance in a minimal number of real-world trials. The proposed research will advance learning and adaptation capabilities of practical cyberphysical systems. The proposed approach will be generally applicable and lead to a new class of learning and adapting systems that are able to leverage shared properties between multiple tasks to significantly speed up learning and adaptation. Success in this research project will bring society closer to solving the grand challenge of teams of mobile, disposable, search and rescue robots which can robustly locomote through uncertain and novel environments, finding survivors in disaster situations, while removing risk from rescuers. This project will provide interdisciplinary training through research and classwork for undergraduate and graduate students in creating systems which intimately couple the cyber and physical aspects in robotic and living mobile platforms. Through the SUPERB summer program, under-represented students in engineering will experience research in learning and robotics.

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 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.