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Cartesian impedance control is a type of motion control strategy for robots that improves safety in partially unknown environments by achieving a compliant behavior of the robot with respect to its external forces. This compliant robot behavior has the added benefit of allowing physical human guidance of the robot. In this paper, we propose a C++ implementation of compliance control valid for any
Graphical poster summary of conference paper.
Mixed-effects models are used to describe the inter-patient variability in drugs. Modeling of these variabilities include both fixed and random effects. Fixed effects relate covariates such as age and weight to compartment volumes and clearances, whereas random effects account for unexplained variability. Traditionally, the development of fixed effects models is an inefficient process where covari
In the mining industry, flotation is a commonly used process to separate valuable minerals from waste rock in a concentrator. The rougher flotation is the first stage of the process and in Boliden AB’s concentrator at Aitik, it consists of two lines of four flotation cells each. In this paper we consider one line and the buffer tank upstream of it. Modeling this process step, and maintaining an up
In this paper, we investigate the problem of decoder error propagation for spatially coupled low-density parity-check (SC-LDPC) codes with sliding window decoding (SWD). This problem typically manifests itself at signal-to-noise ratios (SNRs) close to capacity under low-latency operating conditions. In this case, infrequent but severe decoder error propagation can sometimes occur. To help understa
Research in community ecology has tended to focus on trophic interactions (e.g., predation, resource competition) as driving forces of community dynamics, and sexual interactions have often been overlooked. Here we discuss how sexual interactions can affect community dynamics, especially focusing on frequency-dependent dynamics of horizontal communities (i.e., communities of competing species in a
Clustering multiple motions from observed point trajectories is a fundamental task in understanding dynamic scenes. Most motion models require multiple tracks to estimate their parameters, hence identifying clusters when multiple motions are observed is a very challenging task. This is even aggravated for high-dimensional motion models. The starting point of our work is that this high-dimensionali
This work addresses the design of multi-agent coordination through high-order consensus protocols. While first-order consensus strategies are well-studied—with known robustness to uncertainties such as time delays, time-varying weights, and nonlinearities like saturations—the theoretical guarantees for high-order consensus are comparatively limited. We propose a compositional control framework tha
Neural implicit representations have recently become popular in simultaneous localization and mapping (SLAM), especially in dense visual SLAM. However, existing works either rely on RGB-D sensors or require a separate monocular SLAM approach for camera tracking, and fail to produce high-fidelity 3D dense reconstructions. To address these shortcomings, we present NICER-SLAM, a dense RGB SLAM system
Distributed optimal control is known to be challenging and can become intractable even for linear-quadratic regulator problems. In this work, we study a special class of such problems where distributed state feedback controllers can give near-optimal performance. More specifically, we consider networked linear-quadratic controllers with decoupled costs and spatially exponentially decaying dynamics
Frequent updates in IoT software are crucial for fixing security vulnerabilities, correcting bugs, and adding new features. However, for systems comprising geographically distributed devices, implementing updates is challenging. Such updates must be coordinated across multiple devices, automated without end-user involvement, adaptable to weak connectivity, and minimally disruptive to end users. In
In this work, we consider the problem of coordinating a collection of nth-order integrator systems. The coordination is achieved through the novel serial consensus design; this control design achieves a stable closed-loop system while adhering to the constraint of only using local and relative measurements. Earlier work has shown that second-order serial consensus can stabilize a collection of dou
The optimization of expensive-to-evaluate black-box functions is prevalent in various scientific disciplines. Bayesian optimization is an automatic, general and sample-efficient method to solve these problems with minimal knowledge of the underlying function dynamics. However, the ability of Bayesian optimization to incorporate prior knowledge or beliefs about the function at hand in order to acce
System logs are crucial for understanding the state and health of systems, yet manual inspection becomes impractical due to the high volume of messages. Consequently, machine learning-based log anomaly detection has emerged to automatically identify irregularities. This study investigates the effectiveness of log message embeddings, a novel parsing method, for anomaly detection in complex systems.
This paper deals with the centroid and formation control problem of multi–agent robotic systems. The proposed solution is based on a leader–follower scheme, where only a subset of agents, i.e., the leaders, knows the desired trajectories for the centroid and the formation of the system, while the other agents, i.e., the followers, are required to estimate them through a dynamic consensus scheme. T
This paper presents an in-depth analysis of the stability and performance of control systems experiencing sensor timing misalignments, a common challenge in practical applications such as autonomous vehicles and aerospace systems. We model multichannel sensor delays as independent random variables, capturing the variability of real-world systems where different sensors exhibit distinct and non-con
This study investigated the birth prevalence of cleft lip and/or palate (CL/P) in Sweden between 2000 and 2020 using data from the Swedish National Medical Birth Register, which includes over 97% of children born in the country, and its subregister the National Register of Congenital Anomalies. The dataset included 2,230,771 anonymized children, with the variables year of birth, sex and diagnoses
Logs are prevalent in modern cloud systems and serve as a valuable source of information for system maintenance. Over the years, many supervised, semi-supervised, and unsupervised log analysis methods have been proposed to detect system anomalies. In particular, semi-supervised methods have garnered increasing attention as they balance reduced labeled data requirements and optimal detection perfor
Estimating glomerular filtration rate (GFR) is important in daily practice to assess kidney function and adapting the best clinical care of patients with and without chronic kidney disease. The new creatinine-based European Kidney Function Consortium (EKFC) equation is used to estimate GFR. This equation was developed and validated mainly in European individuals and based on a rescaled creatinine,
Recent methods on privacy-preserving image-based localization use a random line parameterization to protect the privacy of query images and database maps. The lifting of points to lines effectively drops one of the two geometric constraints traditionally used with point-to-point correspondences in structure-based localization. This leads to a significant loss of accuracy for the privacy-preserving
