This paper considers the problem of develo** algorithms for the distributed fusion of
Gaussian mixture models through the use of Chernoff information. We derive a first order …

Summary This Chapter describes Orca: an open-source project which applies Component-
Based Software Engineering principles to robotics. It provides the means for defining and …

Distributed data fusion (DDF) is the process whereby a group of agents sense their local
environment, communicate with other agents, and collectively try to infer knowledge about a …

Some concerns are raised on the prevailing generalized covariance intersection (GCI)
based Gaussian mixture probability hypothesis density (GM-PHD) fusion for distributed …

The use of a sigma-point approximation is proposed for the Chernoff fusion of Gaussian
mixtures. The superiority of the proposed method to its best alternatives in the literature is …

The paper presents two algorithms for Decentralized Bayesian information fusion and
information-theoretic decision making. The algorithms are stated in terms of operations on a …

This paper presents a decentralised particle filtering algorithm that enables multiple vehicles
to jointly track 3D features under limited communication bandwidth. This algorithm, applied …

Decentralized data fusion is a challenging task even for linear estimation problems.
Nonlinear estimation renders data fusion even more difficult as dependencies among the …

An exemplary system and method are for tracking a target in a decentralised network having
a plurality of sensing nodes. Each node makes observations of a target, performs a multiple …

We consider the distributed multitarget tracking over sensor networks, where each node only
communicates with its neighbors. We develop a diffusion-based distributed multisensor …