Distributed optimization provides a framework for deriving distributed algorithms for a variety
of multi-robot problems. This tutorial constitutes the first part of a two-part series on …

Distributed particle filter (DPF) algorithms are sequential state estimation algorithms that are
executed by a set of agents. Some or all of the agents perform local particle filtering and …

In this paper, we consider the problem of Distributed Multi-sensor Multi-target Tracking
(DMMT) for networked fusion systems. Many existing approaches for DMMT use multiple …

Incorporating intelligence in industrial systems can help to increase productivity, cut-off
production costs, and to improve working conditions and safety in industrial environments …

Distribution and decentralisation of fusion operations are key to network centric operations
(NCOs) and distributed data fusion algorithms (DDF) have been developed to support them …

This paper considers situations in which a team of mobile sensor platforms autonomously
explores an environment to detect and localize an unknown number of targets. Individual …

In this paper we address the problem of cooperative localization and target tracking with a
team of moving robots. We model the problem as a least squares minimization problem 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 …

A constrained sufficient statistic (CSS)-based distributed particle filter (CSS/DPF)
implementation is proposed for nonlinear bearing-only and joint bearing/range tracking …

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