The emergence of low-cost, highly-autonomous vehicles equipped with control, communication, sensing and computing capabilities is paving the way for the deployment of mobile sensor networks in a wide range of applications. Examples include environmental monitoring, oceanographic research, high-stress, rapid de- ployment operations, and health monitoring of civil infrastructure. In these envisioned applications, many critical processes occur at temporal and spatial scales that cannot be effectively sampled with current ap- proaches. Mobile sensor networks hold the promise to provide the rich, in-situ spatio-temporal data needed to revolutionize the detection, estimation, and monitoring of dynamic natural phenomena. Controlled mobility integrated with distributed data fusion capabilities will enable sensor networks to provide broad spatial cov- erage, react to short-lived events in real time, and track key processes that occur away from fixed sites. The state of the art in distributed data fusion only considers static networks, and therefore is not directly applicable to ad-hoc, dynamically changing mobile networks. The state of the art in motion coordination of networked systems has only developed centralized approaches to estimation and signal processing. As a result of these limitations, current mobile networks are too rigid to cope with the small-scale features and the rapid evolution characteristic of many key physical processes. Intellectual Merit. The major objective of this project is the synthesis of scalable coordination algorithms for mobile networks performing spatially-distributed sensing tasks. Distributed strategies that maximize the information content of collected data will allow future sensor networks to adapt to changing conditions in a rapid, autonomous and optimal fashion. To make this vision a reality, this project will address the distributed, in-situ aggregation of data collected by mobile networks in dynamic scenarios, and the information-driven, scalable coordination of the network mobility to optimally perform the required sensing tasks. The research plan will adopt an ambitious integrative approach composed of three thrusts: (i) a sound, unifying framework where different cooperative strategies can be rigorously formalized and compared. This effort will facilitate the modular design of cooperative strategies for complex sensing tasks via the combination of simpler algorithms performing more basic objectives; (ii) system-theoretic tools to evaluate the correctness, robustness and scalability properties of coordination algorithms. To assess the optimal trade-offs between performance and energy allocation in combined communication, motion, and sensing scenarios, this research will evaluate complexity measures for cooperative strategies and spatially-distributed tasks; and (iii) novel, systematic design methodologies that allow to break down global sensing tasks into local objectives for individual agents. This effort seeks to synthesize fault tolerant, scalable algorithms that sit at the limits on the achievable performance, operational time and energy consumption of mobile networks conducting data fusion and estimation tasks. The innovative technical approach builds on a set of very promising results by the PI and collaborators, hinging upon disciplines such as cooperative and topology control, automata and hybrid systems theory, robotics, wireless communications, and operations research. Broader Impacts. The techniques developed in this work will help design autonomous and efficient mobile networks performing critical tasks in homeland security, industrial processes, health care and the environment. The proposed research will lead to crosscutting and synergistic technologies applicable to a wide range of scenarios where real-time information gathering and data exploitation are important. The results will be transferred to oceanographic and disaster management applications in collaboration with the Monterey Bay Aquarium Research Institute, and NASA Ames, respectively. The proposed educational activities are integrated into the research plan and consist of the following initiatives: (i) involvement of undergraduate students in research via design projects, summer internships and engineering research demonstrations in a newly-created laboratory environment; (ii) development of an undergraduate course on Motion Coordination" and a graduate course on Cooperative Mobile Networks"; (iii) offering of a course on control and robotics in the California State Summer School for Mathematics and Science for high-school students, and expository and research talks at community colleges near UCSC. Re- search and educational materials will be made available to high-school teachers, the scientific community and the general public via an interactive website. Regular activities for broad dissemination (journal publications, conference presentations, lecture notes) will also be pursued. The evaluation of the educational activities, based on the educational process and the students' outcomes, will be done in collaboration with the UCSC Center for Teaching Excellence. Special attention will be paid to integrate inclusive teaching practices into the daily educational activity to address retention issues concerning underrepresented students.
