Distributed multi-agent magnetic field norm SLAM with Gaussian processes

Accurately estimating the positions of multi-agent systems in indoor environments is challenging due to the lack of Global Navigation Satelite System (GNSS) signals. Noisy measurements of position and orientation can cause the integrated position estimate to drift without bound. Previous research has proposed using magnetic field simultaneous...

Mapping the magnetic field using a magnetometer array with noisy input Gaussian process regression

Ferromagnetic materials in indoor environments give rise to disturbances in the ambient magnetic field. Maps of these magnetic disturbances can be used for indoor localisation. A Gaussian process can be used to learn the spatially varying magnitude of the magnetic field using magnetometer measurements and information about the position of the...

Large-scale magnetic field maps using structured kernel interpolation for Gaussian process regression

We present a mapping algorithm to compute large-scale magnetic field maps in indoor environments with approximate Gaussian process (GP) regression. Mapping the spatial variations in the ambient magnetic field can be used for 10-calization algorithms in indoor areas. To compute such a map, GP regression is a suitable tool because it provides...

Tightly Integrated Motion Classification and State Estimation in Foot-Mounted Navigation Systems

A framework for tightly integrated motion mode classification and state estimation in motion-constrained inertial navigation systems is presented. The framework uses a jump Markov model to describe the navigation system's motion mode and navigation state dynamics with a single model. A bank of Kalman filters is then used for joint inference...

Estimating PV Curtailed Power as a Voltage Support Service using Data-Driven Approaches

To guarantee a successful deployment of a droop-based control strategy to mitigate overvoltage problems caused by solar photovoltaic (PV) generation, Distribution System Operators (DSOs) will need to estimate the amount of active power curtailed by the PV inverters for billing purposes. This paper provides a structural elaboration on the...

A Framework for Indoor Localization Using the Magnetic Field

In this work, our focus is on indoor localization using the indoor magnetic field as a source of position information. This relies on the fact that ferromagnetic materials inside buildings cause the magnetic field to vary spatially. We jointly estimate the pose of a combined sensor module (containing a magnetometer) as well as the magnetic field...

Indoor SLAM using a foot-mounted IMU and the local magnetic field

In this paper, a simultaneous localization and mapping algorithm for tracking the motion of a pedestrian with a foot-mounted inertial measurement unit is proposed. The algorithm uses two maps, namely, a motion map and a magnetic field map. The motion map captures typical motion patterns of pedestrians in buildings that are constrained by e.g....

Quantification of the development of trunk control in healthy infants using inertial measurement units

Trunk motor control is essential for the proper functioning of the upper extremities and is an important predictor of gait capacity in children with delayed development. Early diagnosis and intervention could increase the trunk motor capabilities in later life, but current tools used to assess the level of trunk motor control are largely...

Magnetic field norm SLAM using Gaussian process regression in foot-mounted sensors

We propose an application of magnetic field norm simultaneous localisation and mapping to measurements from a foot-mounted sensor for pedestrian navigation. The algorithm is, to the best of the authors’ knowledge, the first three dimensional drift-compensating indoor navigation method using only accelerometer, gyroscope and magnetometer...

Fast relative sensor orientation estimation in the presence of real-world disturbances

We present a novel approach to estimate the relative sensor orientation from inertial sensors placed on connected body segments. Drift in the relative orientation estimates obtained by integrating the gyroscope measurements is corrected solely by incorporating common information in the inertial sensor measurements due to the connection of the...

Adaptive compensation of measurement delays in multi-sensor fusion for inertial motion tracking using moving horizon estimation

Robust and accurate pose estimation of moving systems is a challenging task that is often tackled by combining information from different sensor subsystems in a multi-sensor fusion setup. To obtain robust and accurate estimates, it is crucial to respect the exact time of each measurement. Data fusion is additionally challenged when the...

On attitude representations for optimization-based Bayesian smoothing

This paper presents a study of the behavior of seven different attitude representations in a batchwise orientation smoothing problem. The representations include the well-known unit quaternions and rotation vectors(/axis-angle), as well as modified Rodrigues parameters (MRPs). We consider error states as well as direct orientation formulations...

Towards in-field and online calibration of inertial navigation systems using moving horizon estimation

Inertial sensors are used in an increasing number of autonomous applications. Integrating such sensors into dynamic systems, the problem of their calibration arises naturally. Existing methods often require the sensor to be accurately placed in certain poses, which can be infeasible in practice. In this paper, we present an optimization-based...

On motions that allow for identification of hinge joint axes from kinematic constraints and 6D IMU data

In inertial motion tracking of kinematic chains, inertial measurement units (IMUs) are attached to each segment in order to track their motion in three-dimensional space. Determining the relations between the functional axes of a joint and the local coordinate system of the attached sensor is a crucial requirement. For the case of hinge...

Scalable magnetic field SLAM in 3D using Gaussian process maps

We present a method for scalable and fully 3D magnetic field simultaneous localisation and mapping (SLAM) using local anomalies in the magnetic field as a source of position information. These anomalies are due to the presence of ferromagnetic material in the structure of buildings and in objects such as furniture. We represent the magnetic...

A method for lower back motion assessment using wearable 6D inertial sensors

Low back pain (LBP) is a leading cause of activity limitation. Objective assessment of the spinal motion plays a key role in diagnosis and treatment of LBP. We propose a method that facilitates clinical assessment of lower back motions by means of a wireless inertial sensor network. The sensor units are attached to the right and left side of...

Articulated Planar Reformation for Change Visualization in Small Animal Imaging

The analysis of multi-timepoint whole-body small animal CT data is greatly complicated by the varying posture of the subject at different timepoints. Due to these variations, correctly relating and comparing corresponding regions of interest is challenging. In addition, occlusion may prevent effective visualization of these regions of interest....