The main objective of this project is the development of a systematic approach to the design of scalable, robust, and adaptive algorithms for a class of dynamic task-based motion coordination problems for large-scale networks of mobile agents. The agents are subject to differential and algebraic constraints on their motion including, for example, non-holonomic dynamics and collision avoidance. Tasks are generated over time by an external source, modeled either as a stochastic or adversarial process, acting independently from the agents' motion. The project will aim at a precise characterization of the closed-loop performance and of the implementation complexity of the algorithms. While the class of problems under consideration falls within the class of stochastic and combinatorial decision systems with uncertain information, a geometric component is added to these problems by explicitly addressing differential and algebraic constraints on the motion of the agents, information exchange, and local sensing of the environment. The proposed approach is based the development of tools combining ideas from systems and control, robotics, combinatorial optimization, and distributed computing. This project addresses the problem of coordinating the motion of a possibly large number of mobile agents, in order to achieve dynamically-changing tasks over a geographically extended region of interest. For example, agents can represent mobile sensors required to collect information about a time-varying spatial field (e.g., temperature profiles, chemical concentration, etc.), or mobile relays providing wireless communication services over a region of interest. The successful completion of this project will facilitate the development of mobile robotic networks with capabilities that are well beyond those offered by current technology, with a precise understanding of how the size of the network affects its performance and its complexity. The availability of possibly large networks of mobile agents, able to collect and disseminate information over an extended volume of space will greatly impact our capabilities in application areas such as environmental monitoring, planetary exploration, search and rescue, traffic congestion management, surveillance, disaster management and national security.
