The Kalman filter—or, more precisely, the extended Kalman filter (EKF)—is a fundamental
engineering tool that is pervasively used in control and robotics and for various estimation …

In this paper, we first consider a simple Bayesian fusion problem in a matrix Lie group, and
propose to tackle it using the unscented transform. The method is then leveraged to derive …

The present paper introduces a novel methodology for Unscented Kalman Filtering (UKF) on
manifolds that extends previous work by the authors on UKF on Lie groups. Beyond filtering …

This paper presents an algorithm for solving the problem of tracking smooth curves by a
fixed wing unmanned aerial vehicle travelling with a constant airspeed and under a constant …

There has been an increasing interest in multi-disciplinary research on multisensor attitude
estimation technology driven by its versatility and diverse areas of application, such as …

Unscented Kalman filters (UKFs) have become popular in the research community. Most
UKFs work only with Euclidean systems, but in many scenarios it is advantageous to …

The presented work is focusing on the wind estimation and airframe identification based on
real flight experiments as part of the SkyScanner project. The overall objective of this project …

Nonlinear Kalman Filter for Multi-Sensor Navigation of Unmanned Aerial Vehicles covers
state estimation development approaches for Mini-UAV. The book focuses on Kalman …

This paper addresses the problem of nonlinear attitude estimation for mini-UAVs and
proposes a novel formulation of the Unscented Kalman Filter (UKF), named Invariant UKF …

A Bayesian filter for rotation groups in 2D and 3D is derived. The prior, propagator, and
measurement probability densities are all assumed to be bandlimited functions on SO (2) or …