Recovering human pose from RGB images and videos has drawn increasing attention in
recent years owing to minimum sensor requirements and applicability in diverse fields such …

This review surveys the current state of the art in the development of unmanned aerial
vehicles, focusing on algorithms for quadrotors. Tremendous progress has been made …

In this paper we generalize the continuous-discrete extended Kalman filter (CD-EKF) to the
case where the state and the observations evolve on connected unimodular matrix Lie …

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 …

In imitation learning, multivariate Gaussians are widely used to encode robot behaviors.
Such approaches do not provide the ability to properly represent end-effector orientation, as …

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 …

Combining visual information with inertial measurements is a popular approach to achieve
robust and autonomous navigation in robotics, specifically in GPS-denied environments. In …

This paper addresses the growing need to process non-Euclidean data, by introducing a
geometric deep learning (GDL) framework for building universal feedforward-type models …

This paper extends frequency domain quantitative electroencephalography (qEEG) methods
pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked …

Fusing visual information with inertial measurements for state estimation has aroused major
interests in recent years. However, combining a robust estimation with computational …