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Your search for "2025" yielded 23074 hits

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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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