Stephan Weiss
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View article: Equivariant symmetries for inertial navigation systems
Equivariant symmetries for inertial navigation systems Open
This paper investigates the problem of inertial navigation system (INS) filter design through the lens of symmetry. The extended Kalman filter (EKF) and its variants have been the staple of INS filtering for 50 years. However, recent advan…
View article: The Difference between the Left and Right Invariant Extended Kalman Filter
The Difference between the Left and Right Invariant Extended Kalman Filter Open
The extended Kalman filter (EKF) has been the industry standard for state estimation problems over the past sixty years. The Invariant Extended Kalman Filter (IEKF) is a recent development of the EKF for the class of group-affine systems o…
View article: Autonomous Control of Redundant Hydraulic Manipulator Using Reinforcement Learning with Action Feedback
Autonomous Control of Redundant Hydraulic Manipulator Using Reinforcement Learning with Action Feedback Open
This article presents an entirely data-driven approach for autonomous control of redundant manipulators with hydraulic actuation. The approach only requires minimal system information, which is inherited from a simulation model. The non-li…
View article: Extracting analytic singular values from a polynomial matrix
Extracting analytic singular values from a polynomial matrix Open
A matrix of transfer functions is, in most cases, known to admit an analytic singular value decomposition (SVD), with singular values that are real-valued but potentially negative on the unit circle. In this contribution, we propose an alg…
View article: Detection of weak transient broadband signals: Subspace and likelihood ratio test approaches
Detection of weak transient broadband signals: Subspace and likelihood ratio test approaches Open
We investigate the detection of a weak transient broadband signal, and compare a polynomial subspace detection approach to a likelihood ratio test. The former is based on an analytic eigenvalue decomposition of the array data in order to d…
View article: Polynomial eigenvalue decomposition for eigenvalues with unmajorised ground truth – Reconstructing analytic dinosaurs
Polynomial eigenvalue decomposition for eigenvalues with unmajorised ground truth – Reconstructing analytic dinosaurs Open
When estimated space-time covariance matrices from finite data, any intersections of ground truth eigenvalues will be obscured, and the exact eigenvalues become spectrally majorised with probability one. In this paper, we propose a novel m…
View article: Scalable analytic eigenvalue extraction from a parahermitian matrix
Scalable analytic eigenvalue extraction from a parahermitian matrix Open
In order to extract the analytic eigenvalues from a parahermitian matrix, the computational cost of the current state-of-the-art method grows factorially with the matrix dimension. Even though the approach offers benefits such as proven co…
View article: AIVIO: Closed-loop, Object-relative Navigation of UAVs with AI-aided Visual Inertial Odometry
AIVIO: Closed-loop, Object-relative Navigation of UAVs with AI-aided Visual Inertial Odometry Open
Object-relative mobile robot navigation is essential for a variety of tasks, e.g. autonomous critical infrastructure inspection, but requires the capability to extract semantic information about the objects of interest from raw sensory dat…
View article: Impact of Estimation Errors of a Matrix of Transfer Functions onto Its Analytic Singular Values and Their Potential Algorithmic Extraction
Impact of Estimation Errors of a Matrix of Transfer Functions onto Its Analytic Singular Values and Their Potential Algorithmic Extraction Open
A matrix of analytic functions A(z), such as the matrix of transfer functions in a multiple-input multiple-output (MIMO) system, generally admits an analytic singular value decomposition (SVD), where the singular values themselves are func…
View article: Computational and Numerical Properties of a Broadband Subspace-Based Likelihood Ratio Test
Computational and Numerical Properties of a Broadband Subspace-Based Likelihood Ratio Test Open
This paper investigates the performance of a likelihood ratio test in combination with a polynomial subspace projection approach to detect weak transient signals in broadband array data. Based on previous empirical evidence that a likeliho…
View article: Polynomial Power Method: An Extension of the Standard Power Method to Para-Hermitian Matrices
Polynomial Power Method: An Extension of the Standard Power Method to Para-Hermitian Matrices Open
This paper expands the concept of the power method to polynomial para-Hermitian matrices in order to extract the principal analytic eigenpair. The proposed technique involves repeatedly multiplying the para-Hermitian matrix by a polynomial…
View article: Development of A Micro-CT Scanner with Dual-Energy Option and Endovascular Contrast Agent Administration Protocol for Fetal and Neonatal Virtual Autopsy
Development of A Micro-CT Scanner with Dual-Energy Option and Endovascular Contrast Agent Administration Protocol for Fetal and Neonatal Virtual Autopsy Open
The rate of parental consent for fetal and perinatal autopsy is decreasing, whereas parents are more likely to agree to virtual autopsy by non-invasive imaging methods. Fetal and perinatal virtual autopsy needs high-resolution and good sof…
View article: Paraunitary approximation of matrices of analytic functions - the polynomial Procrustes problem
Paraunitary approximation of matrices of analytic functions - the polynomial Procrustes problem Open
The best least squares approximation of a matrix, typically e.g. characterising gain factors in narrowband problems, by a unitary one is addressed by the Procrustes problem. Here, we extend this idea to the case of matrices of analytic fun…
View article: Siamese Residual Neural Network for Musical Shape Evaluation in Piano Performance Assessment
Siamese Residual Neural Network for Musical Shape Evaluation in Piano Performance Assessment Open
Understanding and identifying musical shape plays an important role in music education and performance assessment. To simplify the otherwise time- and cost-intensive musical shape evaluation, in this paper we explore how artificial intelli…
View article: Scalable Analytic Eigenvalue Extraction Algorithm
Scalable Analytic Eigenvalue Extraction Algorithm Open
Broadband sensor array problems can be formulated using parahermitian polynomial matrices, and the optimal solution to these problems can be based on the eigenvalue decomposition (EVD) of these matrices. An algorithm has been proposed in t…
View article: Polynomial Eigenvalue Decomposition for Multichannel Broadband Signal Processing: A mathematical technique offering new insights and solutions
Polynomial Eigenvalue Decomposition for Multichannel Broadband Signal Processing: A mathematical technique offering new insights and solutions Open
This article is devoted to the polynomial eigenvalue decomposition (PEVD) and its applications in broadband multichannel signal processing, motivated by the optimum solutions provided by the EVD for the narrowband case [1] , [2] . In gener…
View article: Equivariant Symmetries for Inertial Navigation Systems
Equivariant Symmetries for Inertial Navigation Systems Open
This paper investigates the problem of inertial navigation system (INS) filter design through the lens of symmetry. The extended Kalman filter (EKF) and its variants have been the staple of INS filtering for 50 years. However, recent advan…
View article: Siamese Residual Neural Network for Musical Shape Evaluation in Piano Performance Assessment
Siamese Residual Neural Network for Musical Shape Evaluation in Piano Performance Assessment Open
Understanding and identifying musical shape plays an important role in music education and performance assessment. To simplify the otherwise time- and cost-intensive musical shape evaluation, in this paper we explore how artificial intelli…
View article: AI-Based Multi-Object Relative State Estimation with Self-Calibration Capabilities
AI-Based Multi-Object Relative State Estimation with Self-Calibration Capabilities Open
The capability to extract task specific, semantic information from raw sensory data is a crucial requirement for many applications of mobile robotics. Autonomous inspection of critical infrastructure with Unmanned Aerial Vehicles (UAVs), f…
View article: Signal Compaction Using Polynomial EVD for Spherical Array Processing With Applications
Signal Compaction Using Polynomial EVD for Spherical Array Processing With Applications Open
Multi-channel signals captured by spatially separated sensors often contain a high level of data redundancy. A compact signal representation enables more efficient storage and processing, which has been exploited for data compression, nois…
View article: PoET: Pose Estimation Transformer for Single-View, Multi-Object 6D Pose Estimation
PoET: Pose Estimation Transformer for Single-View, Multi-Object 6D Pose Estimation Open
Accurate 6D object pose estimation is an important task for a variety of robotic applications such as grasping or localization. It is a challenging task due to object symmetries, clutter and occlusion, but it becomes more challenging when …
View article: INSANE: Cross-Domain UAV Data Sets with Increased Number of Sensors for developing Advanced and Novel Estimators
INSANE: Cross-Domain UAV Data Sets with Increased Number of Sensors for developing Advanced and Novel Estimators Open
For real-world applications, autonomous mobile robotic platforms must be capable of navigating safely in a multitude of different and dynamic environments with accurate and robust localization being a key prerequisite. To support further r…
View article: Overcoming Bias: Equivariant Filter Design for Biased Attitude Estimation with Online Calibration
Overcoming Bias: Equivariant Filter Design for Biased Attitude Estimation with Online Calibration Open
Stochastic filters for on-line state estimation are a core technology for autonomous systems. The performance of such filters is one of the key limiting factors to a system's capability. Both asymptotic behavior (e.g.,~for regular operatio…
View article: COP: Control & Observability-aware Planning
COP: Control & Observability-aware Planning Open
In this research, we aim to answer the question: How to combine Closed-Loop State and Input Sensitivity-based with Observability-aware trajectory planning? These possibly opposite optimization objectives can be used to improve trajectory c…
View article: Equivariant Filter Design for Inertial Navigation Systems with Input Measurement Biases
Equivariant Filter Design for Inertial Navigation Systems with Input Measurement Biases Open
Inertial Navigation Systems (INS) are a key technology for autonomous vehicles applications. Recent advances in estimation and filter design for the INS problem have exploited geometry and symmetry to overcome limitations of the classical …
View article: Depth-aware Object Segmentation and Grasp Detection for Robotic Picking Tasks
Depth-aware Object Segmentation and Grasp Detection for Robotic Picking Tasks Open
In this paper, we present a novel deep neural network architecture for joint class-agnostic object segmentation and grasp detection for robotic picking tasks using a parallel-plate gripper. We introduce depth-aware Coordinate Convolution (…