output
20132026
most citedAutomatic Classification of Defective Photovoltaic Module Cells in Electroluminescence Images

564 citations

25 papers

cs.CV2026

Seeing Red, Thinking Bad: Color Bias in Vision Language Models

Kohsuke Ide, Ryousuke Yamada, Yoshihiro Fukuhara +2

Vision language models (VLMs) are increasingly used in industrial decision-making systems, such as recruitment support and recommendation. This motivates careful analysis of how VL…

cs.RO2026

The Evaluation Cost of Task Specialization in Evolutionary Multi-Robot Systems

Paolo Leopardi, Heiko Hamann, Jonas Kuckling +1

Task specialization can improve the efficiency of multi-robot systems (MRSs). Previous works have investigated the emergence of task-specialist robot controllers through evolutiona…

cs.RO2026

On the Cost of Evolving Task Specialization in Multi-Robot Systems

Paolo Leopardi, Heiko Hamann, Jonas Kuckling +1

Task specialization can lead to simpler robot behaviors and higher efficiency in multi-robot systems. Previous works have shown the emergence of task specialization during evolutio…

cs.RO2025★ 21 cited

A roadmap for AI in robotics

Aude Billard, Alin Albu-Schaeffer, Michael Beetz +8

AI technologies, including deep learning, large-language models have gone from one breakthrough to the other. As a result, we are witnessing growing excitement in robotics at the p…

cs.DB2025★ 6 cited

Pruning in Snowflake: Working Smarter, Not Harder

Andreas Zimmerer, Damien Dam, Jan Kossmann +3

Modern cloud-based data analytics systems must efficiently process petabytes of data residing on cloud storage. A key optimization technique in state-of-the-art systems like Snowfl…

cs.RO2025

UPTor: Unified 3D Human Pose Dynamics and Trajectory Prediction for Human-Robot Interaction

Nisarga Nilavadi, Andrey Rudenko, Timm Linder

We introduce a unified approach to forecast the dynamics of human keypoints along with the motion trajectory based on a short sequence of input poses. While many studies address ei…

cs.CL2025★ 7 cited

LLLMs: A Data-Driven Survey of Evolving Research on Limitations of Large Language Models

Aida Kostikova, Zhipin Wang, Deidamea Bajri +3

Large language model (LLM) research has grown rapidly, along with increasing concern about their limitations. In this survey, we conduct a data-driven, semi-automated review of res…

cs.MA2024★ 3 cited

Learning from Evolution: Improving Collective Decision-Making Mechanisms using Insights from Evolutionary Robotics

Tanja Katharina Kaiser

Collective decision-making enables multi-robot systems to act autonomously in real-world environments. Existing collective decision-making mechanisms suffer from the so-called spee…

cs.RO2024★ 3 cited

A Good Foundation is Worth Many Labels: Label-Efficient Panoptic Segmentation

Niclas Vödisch, Kürsat Petek, Markus Käppeler +2

A key challenge for the widespread application of learning-based models for robotic perception is to significantly reduce the required amount of annotated training data while achie…

cs.RO2024★ 17 cited

Automatic Target-Less Camera-LiDAR Calibration From Motion and Deep Point Correspondences

Kürsat Petek, Niclas Vödisch, Johannes Meyer +3

Sensor setups of robotic platforms commonly include both camera and LiDAR as they provide complementary information. However, fusing these two modalities typically requires a highl…

cs.RO2024★ 28 cited

BEVCar: Camera-Radar Fusion for BEV Map and Object Segmentation

Jonas Schramm, Niclas Vödisch, Kürsat Petek +4

Semantic scene segmentation from a bird's-eye-view (BEV) perspective plays a crucial role in facilitating planning and decision-making for mobile robots. Although recent vision-onl…

math.OC2024

Norm-induced Cuts: Outer Approximation for Lipschitzian Constraint Functions

Adrian Göß, Alexander Martin, Sebastian Pokutta +1

In this paper, we consider a finite-dimensional optimization problem minimizing a continuous objective on a compact domain subject to a multi-dimensional constraint function. For t…

cs.CV2023★ 18 cited

Few-Shot Panoptic Segmentation With Foundation Models

Markus Käppeler, Kürsat Petek, Niclas Vödisch +2

Current state-of-the-art methods for panoptic segmentation require an immense amount of annotated training data that is both arduous and expensive to obtain posing a significant ch…

cs.RO2023★ 29 cited

Collaborative Dynamic 3D Scene Graphs for Automated Driving

Elias Greve, Martin Büchner, Niclas Vödisch +2

Maps have played an indispensable role in enabling safe and automated driving. Although there have been many advances on different fronts ranging from SLAM to semantics, building a…

cs.RO2023★ 3 cited

Fast yet predictable braking manoeuvers for real-time robot control

Mazin Hamad, Jesus Gutierrez-Moreno, Hugo T. M. Kussaba +5

This paper proposes a framework for generating fast, smooth and predictable braking manoeuvers for a controlled robot. The proposed framework integrates two approaches to obtain fe…

cs.RO2023★ 11 cited

The Treachery of Images: Bayesian Scene Keypoints for Deep Policy Learning in Robotic Manipulation

Jan Ole von Hartz, Eugenio Chisari, Tim Welschehold +3

In policy learning for robotic manipulation, sample efficiency is of paramount importance. Thus, learning and extracting more compact representations from camera observations is a…

cs.RO2023★ 26 cited

CoVIO: Online Continual Learning for Visual-Inertial Odometry

Niclas Vödisch, Daniele Cattaneo, Wolfram Burgard +1

Visual odometry is a fundamental task for many applications on mobile devices and robotic platforms. Since such applications are oftentimes not limited to predefined target domains…

cs.RO2023★ 15 cited

CoDEPS: Online Continual Learning for Depth Estimation and Panoptic Segmentation

Niclas Vödisch, Kürsat Petek, Wolfram Burgard +1

Operating a robot in the open world requires a high level of robustness with respect to previously unseen environments. Optimally, the robot is able to adapt by itself to new condi…

cs.RO2022★ 45 cited

PADLoC: LiDAR-Based Deep Loop Closure Detection and Registration Using Panoptic Attention

José Arce, Niclas Vödisch, Daniele Cattaneo +2

A key component of graph-based SLAM systems is the ability to detect loop closures in a trajectory to reduce the drift accumulated over time from the odometry. Most LiDAR-based met…

cs.RO2022★ 34 cited

Continual SLAM: Beyond Lifelong Simultaneous Localization and Mapping Through Continual Learning

Niclas Vödisch, Daniele Cattaneo, Wolfram Burgard +1

Robots operating in the open world encounter various different environments that can substantially differ from each other. This domain gap also poses a challenge for Simultaneous L…

eess.AS2020★ 4 cited

Comparison of user models based on GMM-UBM and i-vectors for speech, handwriting, and gait assessment of Parkinson's disease patients

J. C. Vasquez-Correa, T. Bocklet, J. R. Orozco-Arroyave +1

Parkinson's disease is a neurodegenerative disorder characterized by the presence of different motor impairments. Information from speech, handwriting, and gait signals have been c…

cs.CV2018★ 564 cited

Automatic Classification of Defective Photovoltaic Module Cells in Electroluminescence Images

Sergiu Deitsch, Vincent Christlein, Stephan Berger +4

Electroluminescence (EL) imaging is a useful modality for the inspection of photovoltaic (PV) modules. EL images provide high spatial resolution, which makes it possible to detect…

math.FA2015★ 3 cited

Reducibility of invertible tuples to the principal component in commutative Banach algebras

Raymond Mortini, Rudolf Rupp

Let be a complex, commutative unital Banach algebra. We introduce two notions of exponential reducibility of Banach algebra tuples and present an analogue to the Corach-Suárez…

math.RA2014

The ring of real-valued multivariate polynomials: an analyst's perspective

Raymond Mortini, Rudolf Rupp

In this survey we determine an explicit set of generators of the maximal ideals in the ring of polynomials in variables with real coefficients and gi…