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For many years, car antennas of various applications are co-integrated into the roof-mounted “shark fin” module. More recently, both hidden antennas and full glass roofs are becoming trendy in the car industry. Taken together, they point to the integration of car antennas into glass roof being an attractive car antenna solution. However, such a solution is challenging to realize due to the roof gl
The integration of machine learning (ML) into software operations (MLOps) has significantly increased the demand for data to train and test models, making data sharing and reuse essential to mitigate the high costs of data collection and preprocessing. This study aims to advance the understanding of data sharing within an MLOps context by examining the establishment and governance of a data ecosys
Digital control systems introduce unavoidable computational latencies. For some controllers this time delay inhibits practical use, even though they in theory could provide more efficient control. For example, solving an optimization problem each sampling period when using model predictive control. By sampling faster than the computation time and executing independent controllers on distributed ha
Ensuring functional safety is crucial for the deployment of autonomous systems in real-life dynamic environments, as they must operate reliably and safely among humans. However, existing safety systems are designed with a closed-world assumption and can over-constrain the system by shutting down the robot at every safety violation, limiting the robot’s ability to complete its tasks. To address thi
Motivated by the well established idea that collective wisdom is greater than that of an individual, we propose a novel learning dynamics as a sort of companion to the Abelson model of opinion dynamics. Agents are assumed to make independent guesses about the true state of the world after which they engage in opinion exchange leading to consensus. We investigate the problem of finding the optimal
Quadruped robots are currently a widespread platform for robotics research, thanks to powerful Reinforcement Learning controllers and the availability of cheap and robust commercial platforms. However, to broaden the adoption of the technology in the real world, we require robust navigation stacks relying only on low-cost sensors such as depth cameras. This paper presents a first step towards a ro
In this work, we study the problem of estimating the in-ear sound field using microphone measurements at nearby positions. Typically, the sound field is first interpolated to the position of the head under free-field assumptions, followed by filtering through pre-measured head-related transfer functions (HRTFs). While properties of free-field interpolation methods have been well studied with respe
We propose a method for estimating the 3D position of a target point, given multiple measurements of it, using mm-wave radar data. Given azimuth headings and range estimates from posed radar positions, we find the 3D position, using an approximate, but geometrically and statistically meaningful cost. The 3D position is found in an optimal way, using this approximate cost. By deriving the Lagrangia
The application of Agent-Based Modeling and Simulation (ABMS) has few established guidelines and often suffers from insufficient model documentation. We assess the prevalence of best practices associated with different types of model documentation in light of the European Union's AI Act (AI Act). Our analysis reveals that best practices are often implemented together but ultimately reinforce the p
Robotic systems often face execution failures due to unexpected obstacles, sensor errors, or environmental changes. Traditional failure recovery methods rely on predefined strategies or human intervention, making them less adaptable. This paper presents a unified failure recovery framework that combines Vision-Language Models (VLMs), a reactive planner, and Behavior Trees (BTs) to enable real-time
Permanent Magnet Synchronous Motor (PMSM) is a main component in electrical aircraft and electric vehicles. Due to its advantages, it is gaining the attention of manufacturers. This machine is highly efficient and reliable. It has a high torque to weight ratio. Due to its criticality in application, we need to detect the faults at the initiation stage. The faults associated with PMSM can be electr
Our research aims to develop an intelligent control system for optimizing the operation of lighting systems for a jogging track in the countryside by using adaptive control methods, and optimization of built-in lighting control. Through this, lighting systems will be optimized, energy consumption will be minimized and the lighting system will be adapted to be able to handle a larger amount of loca
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This review examines how coordination is infrastructured in digital health ecosystems where technologies, institutions, and practices intersect across organisational and professional boundaries. Drawing on a systematic analysis of the literature, we identify three interdependent infrastructural layers: technological, informational, and institutional, and four recurring processes through which coor
Permanent Magnet Synchronous Motors (PMSMs) are becoming increasingly popular in traction applications. PMSMs have gained popularity due to their efficiency, compactness and excellent features related to control. This is mainly because of the permanent magnet placement in the rotor, which negates any additional rotor excitation, hence reducing energy losses considerably. This makes them more effic
Probed language-based assessments, where individuals describe their states using open-ended responses analyzed with Artificial Intelligence, have shown great promise for written language. But emotions are also conveyed through spoken language which might provide further assessment power to this method. Participants (N=645) were randomly assigned to watch a video clip of a church, shopping mall, or
The electrification of long-haul freight transport is essential for reducing emissions and achieving sustainable mobility. However, battery-electric trucks (BETs) face significant barriers, including limited range, high battery weight, and prolonged charging times, which hinder their widespread adoption for long-distance travel. Electric Road Systems (ERS) offer a compelling solution by providing
