This project, generalizing mean-field approaches from physics and chemistry for integrated design of scalable, network resource aware, distributed control strategies for multi-agent robotic systems, aims to develop macroscopic models that retain salient features of the underlying multi-agent robotic system and use these models in the design of distributed control strategies. For complex cyber physical systems, this promises to provide a novel design methodology that is potentially applicable to a large class of systems and, therefore, will result in foundational knowledge of use to the community at large. This high-risk, high-reward project integrates ideas from physics, chemistry, control theory, and robotics to develop new theoretical foundations for the design, validation, and improvement of coordination strategies for multi-agent robotic systems. The project's intellectual merit lies in the ensemble approach towards the design, validation, and improvement of cyber physical systems. Mean-field methods provide a system-level abstraction of the underlying distributed system while retaining the salient features of the various agent-level interactions. The generalization of these models to ensembles of interacting engineered systems provides new methods for designing distributed controllers that are sensitive to changing network resources and whose performance can be predicted and adjusted to achieve both the desired short-term and long-term performance specifications. Broader Impacts: The broader impacts of this project are twofold. First, the mean-field approach takes into account network resource usage and management, providing an integrated strategy for designing scalable decentralized control and coordination strategies. Second, different from biologically-inspired approaches, the mean-field approach enables the design of distributed coordination strategies whose performance can be systematically predicted and tuned to meet detailed performance specifications. This has the potential to unify various existing multi-agent coordination approaches. The research outcomes will be disseminated through publications in technical conferences and journals and incorporated into the PI's existing undergraduate and graduate curriculum and K-12 outreach efforts targeted at increasing female participation in STEM fields.

Cyber-physical systems (CPS) are becoming the key enabler in many engineering domains from traffic management to autonomous vehicles. Concurrency, failures, and their interactions with the physical environment make it challenging to wrestle a high level of confidence from such systems. This project develops a reusable middleware service which enables the creation of verified and hence reliable distributed CPS by pushing the state-of-the-art in two directions: (1) Existing distributed services cannot be practically implemented because of high communication costs incurred in the face of dynamic failures and changes. This project develops a Group Communication Service (GCS) which can be implemented with reasonable resources and which guarantees automatic recovery after failures (stabilization). (2) Existing verification techniques focus on non-distributed CPS, and in general systems with failures, message delays, etc., are unlikely to be amenable to automated analysis. For applications built with the GCS, the project develops a suite of verification tools that exploit stabilization, compositionality, abstraction-refinement, and delay insensitivity of applications. These core research tasks will lead to fundamental advances in design and verification of hybrid and distributed systems. The outcomes of this project are expected to bolster the dependability of emerging applications in autonomous vehicles and factories, and intelligent surveillance systems, while keeping the development costs acceptable through automation. Through industry collaborations, the research outcomes will be translated into engineering practices. The educational component will provide course and lab modules for graduate, undergraduate, and high-school students with the aim of unifying the physical and the computational viewpoints in the systems curriculum. Through active recruitment and mentoring, women and minority students will be prepared for careers in scientific research.