This paper proposes an efficient implementation of the generalized labeled multi-Bernoulli
(GLMB) filter by combining the prediction and update into a single step. In contrast to an …

An analytic solution to the multi-target Bayes recursion known as the δ-Generalized Labeled
Multi-Bernoulli (δ-GLMB) filter has been recently proposed by Vo and Vo in [“Labeled …

Robot navigation in the environment with obstacles is still a challenging problem. In this
paper, the navigation problems with wheeled mobile robots (WMRs) are reviewed, the …

This paper proposes an efficient implementation of the multi-sensor generalized labeled
multi-Bernoulli (GLMB) filter. Like its single-sensor counterpart, such implementation …

In multiobject inference, the multiobject probability density captures the uncertainty in the
number and the states of the objects as well as the statistical dependence between the …

Precise vehicle positioning is a key element for the development of Cooperative Intelligent
Transport Systems (C-ITS). In this context, we present a distributed processing technique to …

This overview paper describes the particle methods developed for the implementation of the
class of Bayes filters formulated using the random finite set formalism. It is primarily intended …

In this paper we present a general solution for multi-target tracking with superpositional
measurements. Measurements that are functions of the sum of the contributions of the …

Previous labeled random finite set filter developments use a motion model that only
accounts for survival and birth. While such a model provides the means for a multi-object …

Most approaches to robot localization rely on low-level geometric features such as points,
lines, and planes. In this paper, we use object recognition to obtain semantic information …