Robot Analytics: What Do Human-Robot Interaction Traces Tell Us About Learning?

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This doctoral thesis navigates the complex landscape of motion coordination and formation control within teams of rotary-wing Micro Aerial Vehicles (MAVs). Prompted by the intricate demands of real-world applications such as search and rescue or surveillan ...

Edible robots and robotic food — edible systems that perceive, process and act upon stimulation — could open a new range of opportunities in health care, environmental management and the promotion of healthier eating habits. For example, they could enable ...

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

The control possibilities for soft robots have long been hindered by the need for reliable methods to estimate their configuration. Inertial measurement units (IMUs) can solve this challenge, but they are affected by well-known drift issues. This letter pr ...

Informative sample selection in an active learning (AL) setting helps a machine learning system attain optimum performance with minimum labeled samples, thus reducing annotation costs and boosting performance of computer-aided diagnosis systems in the pres ...

This article summarizes the recent advancements in the design, fabrication, and control of microrobotic devices for the diagnosis and treatment of brain disorders. With a focus on diverse actuation methods, we discuss how advancements in materials science ...

Soft robots are being increasingly developed and deployed for underwater applications such as exploration, monitoring, and rescue owing to their innate compliance, mechanical and chemical stability, and waterproof properties. However, they are still predom ...

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

Reinforcement learning (RL) is crucial for learning to adapt to new environments. In RL, the prediction error is an important component that compares the expected and actual rewards. Dopamine plays a critical role in encoding these prediction errors. In my ...

Conversational tutoring systems (CTSs) offer a promising avenue for individualized learning support, especially in domains like persuasive writing. Although these systems have the potential to enhance the learning process, the specific role of learner cont ...

The worldsheet axion plays a crucial role in the dynamics of the Yang-Mills confining flux tubes. According to the lattice measurements, its mass is of order the string tension and its coupling is close to a certain critical value. Using the S-matrix Boots ...

Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's motion remains bounded over a given number of turns. Understanding the feature ...

Motivation is a multifaceted phenomenon that we explore within the framework of decision-making. Through this cognitive process, actions are directed towards specific goals by performing a trade-off between the cost and benefit of an action. The dorsomedia ...

Dielectric Elastomer Actuators (DEAs) have emerged as versatile and promising devices for a multitude of applications, including soft robotics, haptic interfaces, and artificial muscles. DEAs are an interesting soft actuator technology due to their high en ...

Social behaviors such as cooperation are crucial for mammals. A deeper knowledge of the neuronal mechanisms underlying cooperation can be beneficial for people suffering from pathologies with impaired social behavior. Our aim was to study the brain activit ...

Robot Analytics: What Do Human-Robot Interaction Traces Tell Us About Learning?

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Distributed Predictive Formation Control of Autonomous Rotary-Wing Micro Aerial Vehicles

Towards edible robots and robotic food

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Soft Robot Shape Estimation With IMUs Leveraging PCC Kinematics for Drift Filtering

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Small-scale robotic devices for medical interventions in the brain

Edible Soft Actuators based on Konjac Glucomannan for Underwater Operation

Incorporating Projective Geometry into Deep Learning

Unveiling the complexity of learning and decision-making

Evaluating the Impact of Learner Control and Interactivity in Conversational Tutoring Systems for Persuasive Writing

QCD worldsheet axion from the bootstrap

Optimizing Dynamic Aperture Studies with Active Learning

Neurobiological and metabolic basis of motivation and effort-based decision-making - A human 1H-MRS, fMRI and machine learning study

Frequency response of fiber reinforced DEAs

Involvement of prelimbic cortex neurons and related circuits in the acquisition of a cooperative learning by pairs of rats