CAREER: Mothership/Daughtership Architectures for In Situ Science by Robotic Sensor Networks

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The objective of this project is to develop fundamental understanding of control strategies that can exploit the complimentary computation, sensing, and communication capabilities of the members of a mothership/daughtership robotic sensor network performing in situ volumetric sensing. Concepts from networked unmanned systems, cooperative control, controlled mobility in ad hoc networks, motion planning, and optimal distributed sensing are combined to create a new heterogeneous robot team comprised of two classes of robots with significantly different, though complementary, attributes. Research activities are organized into three main thrusts: i.) daughtership control using ordered upwind methods for motion planning in the presence of strong currents and decentralized coverage control for cooperative sampling in the presence of intermittent communication; ii.) mothership control algorithms based on reinforcement learning to provide delay-tolerant networking and stochastic dynamic programming for optimal deployment and reassignment of the daughterships; and iii.) experimental demonstration performed on an indoor robotic sensor network, outdoors on a heterogeneous unmanned aircraft system, and part of field campaigns with atmospheric scientists.The proposed research project will provide new capabilities for in situ volumetric sampling of complex atmospheric phenomena which will lead to a direct improvement in the ability to understand complex environments. This project will have its broadest impact through the applications that will benefit from robotic sensor networks performing in situ science. Collaborations focus on the study of tornadogenesis in severe storms, sea ice change, and spatio-temporal evolution of airmass boundaries. Additionally, research and education are integrated into activities aimed at improving the perception of the engineering field by K-12 students, retaining those students who are initially attracted to engineering, bringing hands-on active learning to several aerial robotic courses, and fostering interaction between scientists and engineering researchers.