The objective of this research is to develop new models of computation for multi-robot systems. Algorithm execution proceeds in a cycle of communication, computation, and motion. Computation is inextricably linked to the physical configuration of the system. Current models cannot describe multi-robot systems at a level of abstraction that is both manageable and accurate. This project will combine ideas from distributed algorithms, computational geometry, and control theory to design new models for multi-robot systems that incorporate physical properties of the systems. The approach is to focus on the high-level problem of exploring an unknown environment while performing designated tasks, and the sub-problem of maintaining network connectivity. Key issues to be studied will include algorithmic techniques for handling ongoing discrete failures, and ways of understanding system capabilities as related to failure rates, geometric assumptions and physical parameters such as robot mobility and communication bandwidth. New metrics will be developed for error rates and robot mobility. Intellectual merit arises from the combination of techniques from distributed algorithms, computational geometry, and control theory to develop and analyze algorithms for multi-robot systems. The project will develop a new class of algorithms and techniques for their rigorous analysis, not only under ideal conditions, but under a variety of error assumptions. The project will test theoretical ideas empirically, on three different multi-robot systems. Broader impacts will include new algorithms for robot coordination, and rigorous understanding of the capabilities of different hardware platforms. Robots are an excellent outreach tool, and provide concrete examples of theory in action.

The objective of this research is to develop new models of computation for multi-robot systems. Algorithm execution proceeds in a cycle of communication, computation, and motion. Computation is inextricably linked to the physical configuration of the system. Current models cannot describe multi-robot systems at a level of abstraction that is both manageable and accurate. This project will combine ideas from distributed algorithms, computational geometry, and control theory to design new models for multi-robot systems that incorporate physical properties of the systems. The approach is to focus on the high-level problem of exploring an unknown environment while performing designated tasks, and the sub-problem of maintaining network connectivity. Key issues to be studied will include algorithmic techniques for handling ongoing discrete failures, and ways of understanding system capabilities as related to failure rates, geometric assumptions and physical parameters such as robot mobility and communication bandwidth. New metrics will be developed for error rates and robot mobility. Intellectual merit arises from the combination of techniques from distributed algorithms, computational geometry, and control theory to develop and analyze algorithms for multi-robot systems. The project will develop a new class of algorithms and techniques for their rigorous analysis, not only under ideal conditions, but under a variety of error assumptions. The project will test theoretical ideas empirically, on three different multi-robot systems. Broader impacts will include new algorithms for robot coordination, and rigorous understanding of the capabilities of different hardware platforms. Robots are an excellent outreach tool, and provide concrete examples of theory in action.

The objective of this inter-disciplinary research is to develop new technologies to transform the streets of a city into a hybrid transportation/communication system, called the Intelligent Road (iRoad), where autonomous wireless devices are co-located with traffic signals to form a wireless network that fuses real-time transportation data from all over the city to make a wide range of new applications possible. The approach is to build new capacities of quantitative bandwidth distribution, rate/delay assurance, and location-dependent security on a pervasive wireless platform through distributed queue management, adaptive rate control, and multi-layered trust. These new capacities lead to transformative changes in the way the transportation monitoring and control functions are designed and operated. Many technical challenges faced by the iRoad system are open problems. New theories/protocols developed in this project will support sophisticated bandwidth management, quality of service, multi-layered trust, and information fusion in a demanding environment where critical transportation functions are implemented. Solving these fundamental problems advances the state of the art in both wireless technologies and transportation engineering. The research outcome is likely to be broadly applicable in other wireless systems. The economic and societal impact of the iRoad system is tremendous at a time when the country is modernizing its ailing transportation infrastructure. It provides a pervasive communication infrastructure and engineering framework to build new applications such as real-time traffic map, online best-route query, intelligent fuel-efficient vehicles, etc. The research results will be disseminated through course materials, academic publication, industry connection, and presentations at the local transportation department.

The objective of this research is to develop truly intelligent, automated driving through a new paradigm that tightly integrates probabilistic perception and deterministic planning in a formal, verifiable framework. The interdisciplinary approach utilizes three interlinked tasks. Representations develops new techniques for constructing and maintaining representations of a dynamic environment to facilitate higher-level planning. Anticipation and Motion Planning develops methods to anticipate changes in the environment and use them as part of the planning process. Verifiable Task Planning develops theory and techniques for providing probabilistic guarantees for high-level behaviors. Ingrained in the approach is the synergy between theory and experiment using an in house, fully equipped vehicle. The recent Urban Challenge showed the current brittleness of autonomous driving, where small perception mistakes would propagate into planners, causing near misses and small accidents; Fundamentally, there is a mismatch between probabilistic perception and deterministic planning, leading to "reactive" rather than "intelligent" behaviors. The proposed research directly addresses this by developing a single, unified theory of perception and planning for intelligent cyber-physical systems. Near term, this research could be used to develop advanced safety systems in cars. The elderly and physically impaired would benefit from inexpensive, advanced automation in cars. Far term, the advanced intelligence could lead to automated vehicles for applications such as cooperative search and rescue. The research program will educate students through interdisciplinary courses in computer science and mechanical engineering, and experiential learning projects. Results will be disseminated to the community including under-represented colleges and universities.

The objective of this research is to investigate how to replace human decision-making with computational intelligence at a scale not possible before and in applications such as manufacturing, transportation, power-systems and bio-sensors. The approach is to build upon recent contributions in algorithmic motion planning, sensor networks and other fields so as to identify general solutions for planning and coordination in networks of cyber-physical systems. The intellectual merit of the project lies in defining a planning framework, which integrates simulation to utilize its predictive capabilities, and focuses on safety issues in real-time planning problems. The framework is extended to asynchronous coordination by utilizing distributed constraint optimization protocols and dealing with inconsistent state estimates among networked agents. Thus, the project addresses the frequent lack of well-behaved mathematical models for complex systems, the challenges of dynamic and partially-observable environments, and the difficulties in synchronizing and maintaining a unified, global world state estimate for multiple devices over a large-scale network. The broader impact involves the development and dissemination of new algorithms and open-source software. Research outcomes will be integrated to teaching efforts and undergraduate students will be involved in research. Underrepresented groups will be encouraged to participate, along with students from the Davidson Academy of Nevada, a free public high school for gifted students. At a societal level, this project will contribute towards achieving flexible manufacturing floors, automating the transportation infrastructure, autonomously delivering drugs to patients and mitigating cascading failures of the power network. Collaboration with domain experts will assist in realizing this impact.

The objective of this research is to develop methods for the operation and design of cyber physical systems in general, and energy efficient buildings in particular. The approach is to use an integrated framework: create models of complex systems from data; then design the associated sensing-communication-computation-control system; and finally create distributed estimation and control algorithms, along with execution platforms to implement these algorithms. A special emphasis is placed on adaptation. In particular, buildings and their environments change with time, as does the way in which buildings are used. The system must be designed to detect and respond to such changes. The proposed research brings together ideas from control theory, dynamical systems, stochastic processes, and embedded systems to address design and operation of complex cyber physical systems that were previously thought to be intractable. These approaches provide qualitative understanding of system behavior, algorithms for control, and their implementation in a networked execution platform. Insights gained by the application of model reduction and adaptation techniques will lead to significant developments in the underlying theory of modeling and control of complex systems. The research is expected to directly impact US industry through the development of integrated software-hardware solutions for smart buildings. Collaborations with United Technologies Research Center are planned to enhance this impact. The techniques developed are expected to apply to other complex cyber-physical systems with uncertain dynamics, such as the electric power grid. The project will enhance engineering education through the introduction of cross-disciplinary courses.

The objective of this research is to understand how pervasive information changes energy production, distribution and use. The design of a more scalable and flexible electric infrastructure, encouraging efficient use, integrating local generation, and managing demand through awareness of energy availability and use over time, is investigated. The approach is to develop a cyber overlay on the energy distribution system in its physical manifestations: machine rooms, buildings, neighborhoods, isolated generation islands and regional grids. A scaled series of experimental energy networks will be constructed, to demonstrate monitoring, negotiation protocols, control algorithms and Intelligent Power Switches integrating information and energy flows in a datacenter, building, renewable energy: farm", and off-grid village. These will be generalized and validated through larger scale simulations. The proposal's intellectual merit is in understanding broadly how information enables energy efficiencies: through intelligent matching of loads to sources, via various levels of aggregation, and by managing how and when energy is delivered to demand, adapted in time and form to available supply. Bi-directional information exchange is integrated everywhere that power is transferred. Broader impacts include training diverse students, such as undergraduates and underrepresented groups, in a new interdisciplinary curriculum in information and energy technologies. Societal impact is achieved by demonstrating dramatic reductions in the carbon footprint of energy and its overall usage, greater penetration of renewables while avoiding additional fossil fuel plants, and shaping a new culture of energy awareness and management. The evolution of Computer Science will be accelerated to meet the challenges of cyber-physical information processing.

Effective response and adaptation to the physical world, and rigorous management of such behaviors through programmable computational means, are mandatory features of cyber physical systems (CPS). However, achieving such capabilities across diverse application requirements surpasses the current state of the art in system platforms and tools. Current computational platforms and tools often treat physical properties individually and in isolation from other cyber and physical attributes. They do not adequately support the expression, integration, and enforcement of system properties that span cyber and physical domains. This results in inefficient use of both cyber and physical resources, and in lower system effectiveness overall. This work investigates novel approaches to these important problems, based on modularizing and integrating diverse cyber-physical concerns that cross-cut physical, hardware, instruction set, kernel, library, and application abstractions. The three major thrusts of this research are 1) establishing foundational models for expressing, analyzing, enforcing, and measuring different conjoined cyber-physical properties, 2) conducting a fundamental re-examination of system development tools and platforms to identify how different application concerns that cut across them can be modularized as cyber-physical system aspects, and 3) developing prototype demonstrations of our results to evaluate further those advances in the state of the art in aspect-oriented techniques for CPS, to help assess the feasibility of broader application of the approach. The broader impact of this work will be through dissemination of academic papers, and open platforms and tools that afford unprecedented integration of cyber-physical properties.

The objective of the proposed research program is to develop, for the first time, the theory and methods needed for the design of networked control systems for chemical processes and demonstrate their application and effectiveness in the context of process systems of industrial importance. The proposed approach to achieving this objective involves the development of a novel mathematical framework based on nonlinear asynchronous systems to model the sensor and actuator network behavior accounting explicitly for the effect of asynchronous and delayed measurements, network communication and actuation. Within the proposed asynchronous systems framework, novel control methods will be developed for the design of nonlinear networked control systems that improve closed-loop stability, performance and robustness. The controller design methods will be based on nonlinear and predictive control theory and will have provable closed-loop properties. The development and implementation of networked control methods which take advantage of sensor and actuator networks is expected to significantly improve the operation and performance of chemical processes, increase process safety and reliability, and minimize the negative economic impact of process failures, thereby impacting directly the US economy. The integration of the research results into advanced-level classes in process control and the writing of a new book on ``Networked Process Control'' will benefit students and researchers in the field. The development of software, short courses and workshops and the on-going interaction of the PIs with an industrial consortium will be the means for transferring the results of this research into the industrial sector. Furthermore, the involvement of a diverse group of undergraduate and graduate students in the research will be pursued.

The objective of this research is to address issues related to the platform revolution leading to a third generation of networked control systems. The approach is to address four fundamental issues: (i) How to provide delay guarantees over communication networks to support networked control? (ii) How to synchronize clocks over networks so as to enable consistent and timely control actions? (iii) What is an appropriate architecture to support mechanisms for reliable yet flexible control system design? (iv) How to provide cross-domains proofs of proper performance in both cyber and physical domains? Intellectual Merit: Currently neither theory nor networking protocols provide solutions for communication with delay constraints. Coordination by time is fundamental to the next generation of event-cum-time-driven systems that cyber-physical systems constitute. Managing delays and timing in architecture is fundamental for cyberphysical systems. Broader Impact: Process, aerospace, and automotive industries rely critically on feedback control loops. Any platform revolution will have major consequences. Enabling control over networks will give rise to new large scale applications, e.g., the grand challenge of developing zero-fatality highway systems, by networking cars traveling on a highway. This research will train graduate students on this new technology of networked control. The Convergence Lab (i) has employed minority undergraduate students, including a Ron McNair Scholar, as well as other undergraduate and high school researchers, (ii) hosts hundreds of high/middle/elementary school students annually in Engineering Open House. The research results will be presented at conferences and published in open literature.