no code implementations • 31 Oct 2023 • Clara Menzen, Eva Memmel, Kim Batselier, Manon Kok
The benefit of our approach comes from the projection to a smaller subspace: It modifies the shape of the basis functions in a way that it sees fit based on the given data, and it allows for efficient computations in the smaller subspace.
no code implementations • 25 Oct 2023 • Thomas Edridge, Manon Kok
In this paper, we investigate how an array of magnetometers can be used to improve the quality of the magnetic field map.
no code implementations • 25 Oct 2023 • Clara Menzen, Marnix Fetter, Manon Kok
Because full GP regression has a complexity that grows cubically with the number of data points, approximations for GPs have been extensively studied.
1 code implementation • 16 May 2023 • Isaac Skog, Gustaf Hendeby, Manon Kok
A framework for tightly integrated motion mode classification and state estimation in motion-constrained inertial navigation systems is presented.
1 code implementation • 17 Oct 2022 • Frida Marie Viset, Rudy Helmons, Manon Kok
As our proposed algorithm is recursive, it can naturally be incorporated into existing algorithms that uses Gaussian process maps for SLAM.
no code implementations • 29 Mar 2022 • Mostafa Osman, Frida Viset, Manon Kok
The algorithm uses two maps, namely, a motion map and a magnetic field map.
no code implementations • 4 Feb 2021 • Manon Kok, Karsten Eckhoff, Ive Weygers, Thomas Seel
Real-time motion tracking of kinematic chains is a key prerequisite in the control of, e. g., robotic actuators and autonomous vehicles and also has numerous biomechanical applications.
no code implementations • 21 Dec 2020 • Clara Menzen, Manon Kok, Kim Batselier
Multiway data often naturally occurs in a tensorial format which can be approximately represented by a low-rank tensor decomposition.
1 code implementation • 10 Apr 2019 • Arno Solin, Manon Kok
Gaussian processes (GPs) provide a powerful framework for extrapolation, interpolation, and noise removal in regression and classification.
no code implementations • 5 Apr 2018 • Manon Kok, Arno Solin
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.
no code implementations • 20 Apr 2017 • Manon Kok, Jeroen D. Hol, Thomas B. Schön
In this tutorial we focus on the signal processing aspects of position and orientation estimation using inertial sensors.
Robotics Systems and Control
no code implementations • 15 Sep 2015 • Arno Solin, Manon Kok, Niklas Wahlström, Thomas B. Schön, Simo Särkkä
Anomalies in the ambient magnetic field can be used as features in indoor positioning and navigation.
1 code implementation • 12 Feb 2015 • Manon Kok, Johan Dahlin, Thomas B. Schön, Adrian Wills
Maximum likelihood (ML) estimation using Newton's method in nonlinear state space models (SSMs) is a challenging problem due to the analytical intractability of the log-likelihood and its gradient and Hessian.