Rigorous Integration of Inertial Navigation with Optical Sensors by Dynamic Networks

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Point identification of causal effects requires strong assumptions that are unreasonable in many practical settings. However, bounds on these effects can often be derived under plausible assumptions. Even when these bounds are wide or cover null effects, t ...

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 ...

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 ...

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, ...

Deep heteroscedastic regression involves jointly optimizing the mean and covariance of the predicted distribution using the negative log-likelihood. However, recent works show that this may result in sub-optimal convergence due to the challenges associated ...

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 ...

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

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 ...

The success of drone missions is incumbent on an accurate determination of the drone pose and velocity, which are collectively estimated by fusing iner- tial measurement unit and global navigation satellite system (GNSS) mea- surements. However, during a G ...

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 ...

Despite the importance and pervasiveness of Wikipedia as one of the largest platforms for open knowledge, surprisingly little is known about how people navigate its content when seeking information. To bridge this gap, we present the first systematic large ...

Is it possible to detect if the sample paths of a stochastic process almost surely admit a finite expansion with respect to some/any basis? The determination is to be made on the basis of a finite collection of discretely/noisily observed sample paths. We ...

We present an extended validation of semi-analytical, semi-empirical covariance matrices for the two-point correlation function (2PCF) on simulated catalogs representative of luminous red galaxies (LRGs) data collected during the initial 2 months of operat ...

This thesis concerns the theory of positive-definite completions and its mutually beneficial connections to the statistics of function-valued or continuously-indexed random processes, better known as functional data analysis. In particular, it dwells upon ...

We present FITCOV an approach for accurate estimation of the covariance of two-point correlation functions that requires fewer mocks than the standard mock-based covariance. This can be achieved by dividing a set of mocks into jackknife regions and fitting ...

Measurements of large-scale structure (LSS), as performed on the largest 3D map of over two million extragalactic sources from the Sloan Digital Sky Survey, together with measurements of the cosmic microwave background (CMB) anisotropies, are in complete a ...

Context. We present a novel approach to the construction of mock galaxy catalogues for large-scale structure analysis based on the distribution of dark matter halos obtained with effective bias models at the field level. Aims. We aim to produce mock galaxy ...

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 ...

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 ...

Rigorous Integration of Inertial Navigation with Optical Sensors by Dynamic Networks

Chat with Graph Search

Improved bounds and inference on optimal regimes

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

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

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

TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

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

Random matrix methods for high-dimensional machine learning models

Spectral Estimators for High-Dimensional Matrix Inference

Identifying aerodynamics of small fixed-wing drones using inertial measurements for model-based navigation

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

A Large-Scale Characterization of How Readers Browse Wikipedia

Detecting whether a stochastic process is finitely expressed in a basis

Validation of semi-analytical, semi-empirical covariance matrices for two-point correlation function for early DESI data

Positive Definite Completions and Continuous Graphical Models

The two-point correlation function covariance with fewer mocks

Probing the nature of Dark Energy through the study of large scale structures using spectroscopic surveys and their simulations

DESI mock challenge Halo and galaxy catalogues with the bias assignment method

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

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