Abstract

Adding mobility to sensor networks potentially allows them to spatially reconfigure in order adapt to the dynamics of their environment. Such sensor networks with robotic nodes are an instance of a large-scale distributed control problem. We have spent the last several years developing algorithms for distributed sensing (e.g. mapping), and state estimation (e.g. localization) using such networks. I will discuss a variety of such algorithms, with emphasis on those inspired by Physical
models.