The advances in low-latency communications networks and the ever-growing amount of
devices offering localization and navigation capabilities opened a number of opportunities to …

Tight integration algorithms fusing Global Navigation Satellite System (GNSS) and Inertial
Navigation System (INS) have become popular in many high-accuracy positioning and …

Aimed at improving the nonlinear integrated navigation solution performance of multiple low-
cost sensors fusion, this paper presents a multilayer loosely-coupled, local-global, and step …

In the last decades, the increasing complexity of the fusion of proprioceptive and
exteroceptive sensors with Global Navigation Satellite System (GNSS) has motivated the …

In this paper, the effects of wheel slip compensation in trajectory planning for mobile tractor-
trailer robot applications are investigated. Firstly, a kinematic model of the proposed robot …

In this paper, we develop a hybrid Bayesian filter for GNSS and visual odometry (VO) fusion
in urban environments that combines the tracking efficiency of Kalman filter with the superior …

The essential of navigation, perception, and decision-making which are basic tasks for
intelligent robots, is to estimate necessary system states. Among them, navigation is …

This work proposes a marginalised particle filter with variational inference for non‐linear
state‐space models (SSMs) with Gaussian mixture noise. A latent variable indicating the …

Rao-Blackwellized particle filter (RBPF) algorithm aims to solve the Simultaneous
Localization and Mapping (SLAM) problem. The performance of RBPF is based on the …

This letter presents a methodology to reduce the computational burden of Particle Filters
(PF) used to achieve a target state estimation accuracy in Bayesian tracking problems. A …