The rapid development of robotics has enabled legged robots capable of performing highly dynamic tasks such as walking ...

Multi-agent reinforcement learning (MARL) remains difficult to scale to many agents. Recent MARL using Mean Field ...

The objective of this ongoing project is the continuous development and advancement of effective simulation methods for ...

General-purpose intelligent robots are expected to simultaneously handle multiple tasks while interpreting various ...

During keyboard typing, hand and finger movements induce alterations in Wi-Fi signal propagation, reflected in Channel ...

Understanding the underlying reward mechanisms of human locomotion and transferring this knowledge to humanoid robots is ...

The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...

In robotic applications such as autonomous driving and whole-body control, ensuring safety is of utmost importance ...

Robotics platforms can massively benefit from novel Deep Reinforcement Learning approaches. However, robotics have ...

Acoustic keylogging describes a category of side-channel attacks that recover typed keystrokes from audio-streams of ...

Lightweight Cryptography is about developing and analyzing algorithms that provably obtain security goals, such as ...

Visuotactile sensors are gaining momentum in robotics because they provide high-resolution contact measurements at a ...

Motion planning is a crucial component of autonomous robot systems. It addresses the problem of finding a feasible ...

Reinforcement Learning (RL) is a promising tool for solving complicated control and decision-making tasks in a data ...

Autonomous robots need to be able to identify and recognize objects in a scene. For this crucial task we need to ...

Planning algorithms have shown impressive performance in many domains such as chess and Go. In particular, Monte Carlo ...

In recent years, reinforcement learning and its multi-agent analogue have achieved great success in solving various ...

Detailed multi-scale modelling provides in-depth insights into the complex phenomena of catalytic systems that typically ...

X-ray Absorption Spectroscopy (XAS) is a pivotal technique in material research, requiring numerous sampling points for ...

Robotic manipulation stands as a largely unsolved problem despite significant advances in robotics and machine learning ...

Autonomous robotic assembly requires a well-orchestrated sequence of high-level actions and smooth manipulation ...

The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...

Achieving long-horizon dexterous manipulation remains a challenging problem in robotics. There exists a long history of ...

Natural visuomotor control tasks such as pouring liquids into cups are trivial for humans but are challenging to model ...

In wireless communications, beamforming is utilized for the reception and transmission of directional wireless signals ...

Transcription is the process of converting DNA into RNA and is essential to cellular life. The transcription process ...

Deep Learning is the major component of the success of most new Artificial Intelligence applications. A new promising ...

Within the last decade, deep neural networks have attracted much attention from academia and industry. Such a wide ...

Normative computational models of human sensorimotor behavior based on optimal feedback control with signal-dependent ...

Modeling interaction dynamics to generate robot trajectories that enable a robot to adapt and react to a human’s actions ...