The goal of this project is to develop a new framework where teams of mobile robots self-engineer the structure of their communication network in order to improve on the performance of distributed algorithms used for team coordination. The key idea that enables this work is the representation of the network structure in terms of metrics that depend on the full eigenvalue spectrum of the network's adjacency and Laplacian matrices, but can be approximated in a very efficient and decentralized way. These metrics can then be related to the performance of popular, distributed, coordination algorithms, such as consensus, gossiping, and viral information dissemination. The intellectual merit of this research lies in the development of a hybrid network of mobile robots that is controlled jointly in the space of network configurations and robot positions. The study of the integrated system requires the synthesis of new theoretical results drawing from control theory, spectral graph theory, wireless networking, and optimization. This hybrid network combines the following interrelated objectives: Spectral analysis and distributed control of robot networks; Integrated network and mobility control; Richer models of the communication space; Platform deployment and validation.
Successful completion of this research will provide these necessary components in facilitating the design of mobile autonomous systems and fostering their adoption. Wide availability of such systems can have a significant societal impact on, e.g., search, rescue and recovery operations, environmental monitoring for homeland security, or surveillance and reconnaissance missions. The broader impact of this project lies on disseminating the research output in the industry and academia.
