Calibration Aspects of INS Navigation

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The evolution of airborne mapping witnesses the introduction of hybrid lidar-camera systems to enhance data collection, i.e. to obtain simultaneously high-density point-cloud and texture. Yet, the common adjustment of both optical data streams is a nontriv ...

Navigation of drones is predominantly based on sensor fusion algorithms. Most of these algorithms make use of some form of Bayesian filtering with a majority employing an Extended Kalman Filter (EKF), wherein inertial measurements are fused with a Global N ...

Autonomous navigation of small UAVs is typically based on the integration of inertial navigation systems (INS) together with global navigation satellite systems (GNSS). However, GNSS signals can face various forms of interference affecting their continuous ...

This study aims to identify an optimal, as well as practical, parametric structure for a delta-wing UAV aerodynamic model for the purpose of model-based navigation. We present a comprehensive procedure for characterizing the aerodynamics of this platform, ...

This article investigates the performance and accuracy of continuous Real-Time Kinematic (RTK) Global Navigation Satellite System (GNSS) position tracking for hydromorphological surveys, based on a comprehensive river restoration monitoring campaign. The a ...

Tightly-coupled sensor orientation, i.e. the simultaneous processing of temporal (GNSS and raw inertial) and spatial (image and lidar) constraints in a common adjustment, has demonstrated significant improvement in the quality of attitude determination wit ...

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

We perform an error analysis of a fully discretised Streamline Upwind Petrov Galerkin Dynamical Low Rank (SUPG-DLR) method for random time-dependent advection-dominated problems. The time integration scheme has a splitting-like nature, allowing for potenti ...

TimberSLAM (TSLAM) is an object-centered, tag-based visual self-localization and mapping (SLAM) system for monocular RGB cameras. It was specifically developed to support a robust and augmented reality pipeline for close-range, noisy, and cluttered fabrica ...

Drones hold promise to assist in civilian tasks. To realize this application, future drones must operate within large cities, covering large distances while navigating within cluttered urban landscapes. The increased efficiency of winged drones over rotary ...

Electrochemical Impedance Spectroscopy (EIS) and Equivalent Circuit Models (ECMs) are widely used to characterize the impedance and estimate parameters of electrochemical systems such as batteries. We use a generic ECM with ten parameters grouped to model ...

Consider the wave equation with heterogeneous coefficients in the homogenization regime. At large times, the wave interacts in a nontrivial way with the heterogeneities, giving rise to effective dispersive effects. The main achievement of the present wor ...

The p-Laplacian problem -del & sdot; ((mu + |del u|(p-2))del u) = f is considered, where mu is a given positive number. An anisotropic a posteriori residual-based error estimator is presented. The error estimator is shown to be equivalent, up to higher ord ...

In inverse problems, the task is to reconstruct an unknown signal from its possibly noise-corrupted measurements. Penalized-likelihood-based estimation and Bayesian estimation are two powerful statistical paradigms for the resolution of such problems. They ...

Situational awareness strategies are essential for the reliable and secure operation of the electric power grid which represents critical infrastructure in modern society. With the rise of converter-interfaced renewable generation and the consequent shift ...

We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical problem of estimating a bounded mean. Our approach generalizes and improves on the celebrated Chernoff method, yielding the best closed-form "empirical-Bernstein" CSs and ...

The control possibilities for soft robots have long been hindered by the need for reliable methods to estimate their configuration. Inertial measurement units (IMUs) can solve this challenge, but they are affected by well-known drift issues. This letter pr ...

We study the problem of learning unknown parameters in stochastic interacting particle systems with polynomial drift, interaction, and diffusion functions from the path of one single particle in the system. Our estimator is obtained by solving a linear sys ...

This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs ...

In the Large Hadron Collider, the beam losses are continuously measured for machine protection. By design, most of the particle losses occur in the collimation system, where the particles with high oscilla-tion amplitudes or large momentum error are scrape ...

Calibration Aspects of INS Navigation

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On the Perspectives of Image-to-Lidar Constraints in Dynamic Network Optimisation

VDMNav: Software Architecture for Aerodynamically Constrained Navigation on Small Fixed-Wing Drones

VDM-based navigation for Delta-wing UAVs: Models, calibration, implementation

Aerodynamic modeling of a delta-wing UAV for model-based navigation

Performance and accuracy of cross‐section tracking methods for hydromorphological habitat assessment in wadable rivers with sparse canopy conditions

Airborne sensor fusion: Expected accuracy and behavior of a concurrent adjustment

Spectral Estimators for High-Dimensional Matrix Inference

Error estimates for SUPG-stabilised Dynamical Low Rank Approximations

TSLAM: a tag-based object-centered monocular navigation system for augmented manual woodworking

Accurate and agile flight with winged drones

On the use of Cramér-Rao Lower Bound for least-variance circuit parameters identification of Li-ion cells

A Spectral Ansatz for The Long-Time Homogenization of The Wave Equation

Anisotropic Adaptive Finite Elements for a p-Laplacian Problem

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Functional-Basis Analysis of Non-Stationary Signals in Modern Power Grids: Theory and Implementation in Embedded Systems

Anthony C Davison and Igor Rodionov's contribution to the Discussion of 'Estimating means of bounded random variables by betting' by Waudby-Smith and Ramdas

Soft Robot Shape Estimation With IMUs Leveraging PCC Kinematics for Drift Filtering

A Method of Moments Estimator for Interacting Particle Systems and their Mean Field Limit

Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

Data-driven modeling of beam loss in the LHC