This project develops distributed control algorithms for robot sensor networks using information dynamics to unify network mobility and communication. The new framework moves beyond location-based mobility control algorithms and packet-based communication protocols to a single information-theoretic approach. The framework is developed through: (1) formulation of a new quality of service of information metric and characterization of feasible quality of service demands, (2) adaptive receding horizon control that adjusts planning horizon and sample time based on information dynamics, (3) distributed calculation and optimization of team quality of service, and (4) experimental validation using a heterogeneous indoor robot sensor network and outdoor unmanned aircraft systems.
This research enables the collection of in situ data over large spatiotemporal scales. When deployed in remote or hazardous locations the data collected with these networks leads to a direct improvement to model or understand complex environments, which can help save lives. Students will benefit from the multi-disciplinary activities involved, including embedded computing, miniature sensor devices, wireless networking, and automatic control.
