2014 Poster Sessions : On the Fundamental Limitations of Performance for Distributed Decision-Making in Robotic Networks

Student Name : Federico Rossi
Advisor : Marco Pavone
Research Areas: Information Systems
Abstract:
We study fundamental limitations of performance for distributed decision-making in robotic networks. The class of decision-making problems we consider encompasses a number of prototypical problems such as average-based consensus as well as distributed optimization, leader election, majority voting on a limited number of options, MAX, MIN, and logical formulas. We first propose a formal model for distributed computation on robotic networks that is based on the concept of I/O automata and is inspired by the Computer Science literature on distributed computing clusters. Then, we present a number of bounds on time, message, and byte complexity, which we use to discuss the relative performance of a number of approaches for distributed decision-making. From a methodological standpoint, our work sheds light on the relation between the tools developed by the Computer Science and Controls communities on the topic of distributed algorithms.

Bio:
Federico Rossi is a Ph.D. candidate with professor Pavone's Autonomous Systems Lab at Stanford University's Department of Aeronautics and Astronautics. His current research focuses on identifying fundamental limitations of distributed control and matching optimal algorithms for aerospace applications. He holds a M.Sc. (Hons.) in Space Engineering and a B.Sc. (Hons.) in Aerospace Engineering from Politecnico di Milano, Italy. His research interests include distributed control systems, optimization and robotics.