Automatic Identification and Calibration of Stochastic Parameters in Inertial Sensors

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.

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 ...

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 ...

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 ...

Inertial measurement unit (IMU) sensors are widely used for motion analysis in sports and rehabilitation. The attachment of IMU sensors to predefined body segments and sides (left/right) is complex, time-consuming, and error-prone. Methods for solving the ...

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 ...

This paper presents the experimental validation of a linear recursive state estimation (SE) process for hybrid AC/DC microgrids proposed in the authors' previous work. The SE uses a unified and linear measurement model that relies on the use of synchronize ...

Smartphones enable understanding human behavior with activity recognition to support peoples daily lives. Prior studies focused on using inertial sensors to detect simple activities (sitting, walking, running, etc.) and were mostly conducted in homogeneous ...

The usual explanation of the efficacy of wavelet-based methods hinges on the sparsity of many real-world objects in the wavelet domain. Yet, standard wavelet-shrinkage techniques for sparse reconstruction are not competitive in practice, one reason being t ...

Objective. Powered lower-limb prostheses relying on decoding motor intentions from non-invasive sensors, like electromyographic (EMG) signals, can significantly improve the quality of life of amputee subjects. However, the optimal combination of high decod ...

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 ...

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 ...

The estimation of the orientation of an object, and a human head in particular, can be defined by the Euler angles: the yaw, pitch and roll. The robust and drift-free estimation of those angles is usually achieved with the data from several sensors such as ...

For high-impact devices, subsequent vibrations have as much influence on the deterioration of the mechanical structure as the impact itself. To mitigate the consequences of both impacts and resulting vibrations, it is crucial to accurately understand the p ...

We consider expected performances based on max-stable random fields and we are interested in their derivatives with respect to the spatial dependence parameters of those fields. Max-stable fields, such as the Brown-Resnick and Smith fields, are very popula ...

As one of the three most popular sports in the Summer Olympics, competitive swimming has always been an attractive subject of study for sports scientists. The intricate nature of the swimmer's movements and the variety of techniques have led coaches to req ...

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) ...

We propose nonparametric estimators for the second-order central moments of possibly anisotropic spherical random fields, within a functional data analysis context. We consider a measurement framework where each random field among an identically distribute ...

Microelectromechanical system (MEMS) devices, such as accelerometers, are widely used across industries, including the automotive, consumer electronics, and medical industries. MEMS are efficiently produced at very high volumes using large-scale semiconduc ...

With the objective of improving the registration of lidar point clouds produced by kinematic scanning systems, we propose a novel trajectory adjustment procedure that leverages on the automated extraction of selected reliable 3D point–to–point corresponden ...

Spectral-based graph neural networks (SGNNs) have been attracting increasing attention in graph representation learning. However, existing SGNNs are limited in implementing graph filters with rigid transforms and cannot adapt to signals residing on graphs ...

Automatic Identification and Calibration of Stochastic Parameters in Inertial Sensors

Chat with Graph Search

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

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

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

Automatic Body Segment and Side Recognition of an Inertial Measurement Unit Sensor during Gait

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

Experimental Validation of a Unified and Linear State Estimation Method for Hybrid AC/DC Microgrids

Complex Daily Activities, Country-Level Diversity, and Smartphone Sensing: A Study in Denmark, Italy, Mongolia, Paraguay, and UK

The Sparsity of Cycle Spinning for Wavelet-Based Solutions of Linear Inverse Problems

Early decoding of walking tasks with minimal set of EMG channels

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

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

Human Head Yaw Estimation based on Two 3-axis Accelerometers

An Inertial Uni-Axial Interferometer-Based Accelerometer for Harsh Environments

Stochastic derivative estimation for max-stable random fields

SmartSwim: A novel approach to swimming analysis and coaching assistance based on wearable inertial sensors

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

Functional estimation of anisotropic covariance and autocovariance operators on the sphere

Micro 3D printing of a functional MEMS accelerometer

Lidar point-to-point correspondences for rigorous registration of kinematic scanning in dynamic networks

Graph Neural Networks With Lifting-Based Adaptive Graph Wavelets