CPS: Medium: Collaborative Research: Dynamic Routing and Robotic Coordination for Oceanographic Adaptive Sampling
Lead PI:
Francesco Bullo
Co-Pi:
Abstract
The objective of this research is the design of innovative routing, planning and coordination strategies for robot networks, and their application to oceanography. The approach is organized in three synergistic thrusts: (1) the application of queueing theory and combinatorial techniques to networked robots performing sequential tasks, (2) the design of novel distributed optimization and coordination schemes relying only on asynchronous and asymmetric communication, (3) the design of practical routing and coordination algorithms for the USC Networked Aquatic Platforms. In collaboration with oceanographers and marine biologists, the project aims to design motion, communication and interaction protocols that maximize the amount of scientific information collected by the platforms. This proposal addresses multi-dimensional problems of relevance in Engineering and Computer Science by unifying fundamental concepts from multiple cyberphysical domains (robotics, autonomy, combinatorics, and network science). Our team has expertise in a broad range of scientific disciplines, including control theory and theoretical computer science and their applications to multi-agent systems, robotics and sensor networks. The proposed research will have a positive impact on the emerging technology of autonomous and reliable robotic networks, performing a broad range of environmental monitoring and logistic tasks. Our educational and outreach objectives are manifold and focus on (1) integrating the proposed research themes into undergraduate education and research, e.g., via the existing NSF REU site at the USC Computer Science Department, and (2) mounting a vigorous program of outreach activities, e.g., via a well-developed collaboration with the UCSB Center for Science and Engineering Partnerships.
Francesco Bullo
Performance Period: 09/15/2010 - 08/31/2015
Institution: University of California-Santa Barbara
Sponsor: National Science Foundation
Award Number: 1035917