Research online: Robust tightly coupled GNSS/INS estimation for navigation

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Selection bias may arise when data have been chosen in a way that subsequent analysis does not account for. Such bias can arise in climate event attribution studies that are performed rapidly after a devastating "trigger event'', whose occurrence correspon ...

Background: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validat ...

We introduce Neural Network (NN for short) approximation architectures for the numerical solution of Boundary Integral Equations (BIEs for short). We exemplify the proposed NN approach for the boundary reduction of the potential problem in two spatial dime ...

This paper considers the problem of second-degree price discrimination when the type distribution is unknown or imperfectly specified by means of an ambiguity set. As robustness measure we use a performance index, equivalent to relative regret, which quant ...

The digitization of library resources and services have opened up physical informational spaces to new dimensions by allowing users to access a wealth of documents in ways that di昀昀er from browsing bookshelves traditionally organized according to the "tree ...

The Vehicle Dynamic Model (VDM) based navigation of fixed-wing drones determines the airborne trajectory in conjunction with Inertial Measurement Unit (IMU) sensors. Without Global Navigation Satellite Systems (GNSS) signals, this method estimates navigati ...

Inspired by Sibson’s alpha-mutual information, we introduce a new parametric class of universal predictors. This class interpolates two well-known predictors, the mixture estimator, that includes the Laplace and the Krichevsky-Trofimov predictors, and the ...

We study the problem of learning unknown parameters of stochastic dynamical models from data. Often, these models are high dimensional and contain several scales and complex structures. One is then interested in obtaining a reduced, coarse-grained descript ...

Safety-critical navigation applications require that estimation errors be reliably quantified and bounded. Over the last decade, significant effort has been put to guarantee a bounded position estimation by using Global Navigation Satellite Systems (GNSS) ...

In airborne laser scanning a high-frequency trajectory solution is typically determined from inertial sensors and employed to directly geo-reference the acquired laser points. When low-cost MEMS inertial sensors are used, such as in lightweight unmanned ae ...

In this work, we consider the problem of estimating the probability distribution, the quantile or the conditional expectation above the quantile, the so called conditional-value-at-risk, of output quantities of complex random differential models by the MLM ...

Assessing the traversability of rugged terrain is a difficult challenge for legged robots, especially when they implement multiple, distinct gaits. We tackle this problem on the k-rock2 amphibious, sprawling gait robot by training a gait-dependent traversa ...

Research online: Robust tightly coupled GNSS/INS estimation for navigation

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Timing and spatial selection bias in rapid extreme event attribution

Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium

ReLU Neural Network Galerkin BEM

Price Discrimination with Robust Beliefs

A Topological Data Analysis of Navigation Paths within Digital Libraries

Optimization and Real-Time Aspects of Aircraft Model-Based Navigation

Alpha-NML Universal Predictors

Filtered data and eigenfunction estimators for statistical inference of multiscale and interacting diffusion processes

GNSS/INS Kalman Filter Integrity Monitoring with Uncertain Time Correlated Error Processes

On the benefit of concurrent adjustment of active and passive optical sensors with GNSS & raw inertial data

Quantifying uncertain system outputs via the multi-level Monte Carlo method --- distribution and robustness measures

Gait-dependent Traversability Estimation on the k-rock2 Robot