Underwater surveillance has traditionally been carried out by means of surface and
undersea manned vessels equipped with advanced sensor systems. This approach is often …

This self-contained introduction to the distributed control of robotic networks offers a
distinctive blend of computer science and control theory. The book presents a broad set of …

The problem of distributed Kalman filtering (DKF) for sensor networks is one of the most
fundamental distributed estimation problems for scalable sensor fusion. This paper …

Recent advances in technology are delivering robots of reduced size and cost. A natural
outgrowth of these advances are systems comprised of large numbers of robots that …

One of the fundamental problems in sensor networks is to estimate and track the state of
targets (or dynamic processes) of interest that evolve in the sensing field. Kalman filtering …

The problem of target localization involves estimating the position of a target from multiple
noisy sensor measurements. It is well known that the relative sensor-target geometry can …

The ability of a robot team to reconfigure itself is useful in many applications: for
metamorphic robots to change shape, for swarm motion towards a goal, for biological …

The direct measurement of external loads acting on structures remains a challenge in many
engineering applications. In this context, mechanical load identification has received …

Reliable and accurate position information is of great importance for many mass-market and
emerging applications. Network localization and navigation (NLN) is a promising paradigm …

In this paper, we introduce a theoretical framework for coupled distributed estimation and
motion control of mobile sensor networks for collaborative target tracking. We use a Fisher …