93 citations · 202 across the 37 of their papers we have counts for
39 papers
When to Make a Decision: Task-Sufficient Active Perception for Mobile Manipulator Robots
Mariana da Silva Barros, Matthias Kerzel, Cornelius Weber +1
A robotic agent operating in an unknown environment must gather sufficient task-relevant information before acting. However, determining when the available information is sufficien…
SmoLSTM: A Compact Vision-Language-Action Model with Recurrent Memory that Persists
Jan-Gerrit Habekost, Parsa Mastouri Kashani, Connor Gäde +5
Vision-language-action models often predict actions from only the current observation, which can leave tasks involving object occlusion or visually identical objects ambiguous with…
MoDiCoL: A Modular Diagnostic Continual Learning Dataset for Robust Speech Recognition
Theresa Pekarek Rosin, Matthias Kerzel, Stefan Wermter
Modern Automatic Speech Recognition (ASR) systems have made remarkable progress on standard benchmarks, yet performance gaps have emerged under real-world distribution shifts, caus…
Uncertainty, Vagueness, and Ambiguity in Human-Robot Interaction: Why Conceptualization Matters
Xiaowen Sun, Cornelius Weber, Matthias Kerzel +2
Uncertainty, vagueness, and ambiguity are closely related and often confused concepts in human-robot interaction (HRI). In earlier studies, these concepts have been defined in cont…
Theory of Mind for Explainable Human-Robot Interaction
Marie S. Bauer, Julia Gachot, Matthias Kerzel +2
Within the context of human-robot interaction (HRI), Theory of Mind (ToM) is intended to serve as a user-friendly backend to the interface of robotic systems, enabling robots to in…
Talking to Robots: A Practical Examination of Speech Foundation Models for HRI Applications
Theresa Pekarek Rosin, Julia Gachot, Henri-Leon Kordt +2
Automatic Speech Recognition (ASR) systems in real-world settings need to handle imperfect audio, often degraded by hardware limitations or environmental noise, while accommodating…
Investigating Pedagogical Teacher and Student LLM Agents: Genetic Adaptation Meets Retrieval Augmented Generation Across Learning Style
Debdeep Sanyal, Agniva Maiti, Umakanta Maharana +4
Effective teaching requires adapting instructional strategies to accommodate the diverse cognitive and behavioral profiles of students, a persistent challenge in education and teac…
Shaken, Not Stirred: A Novel Dataset for Visual Understanding of Glasses in Human-Robot Bartending Tasks
Lukáš Gajdošech, Hassan Ali, Jan-Gerrit Habekost +3
Datasets for object detection often do not account for enough variety of glasses, due to their transparent and reflective properties. Specifically, open-vocabulary object detectors…
DIRIGENt: End-To-End Robotic Imitation of Human Demonstrations Based on a Diffusion Model
Josua Spisak, Matthias Kerzel, Stefan Wermter
There has been substantial progress in humanoid robots, with new skills continuously being taught, ranging from navigation to manipulation. While these abilities may seem impressiv…
Details Make a Difference: Object State-Sensitive Neurorobotic Task Planning
Xiaowen Sun, Xufeng Zhao, Jae Hee Lee +3
The state of an object reflects its current status or condition and is important for a robot's task planning and manipulation. However, detecting an object's state and generating a…
Diffusing in Someone Else's Shoes: Robotic Perspective Taking with Diffusion
Josua Spisak, Matthias Kerzel, Stefan Wermter
Humanoid robots can benefit from their similarity to the human shape by learning from humans. When humans teach other humans how to perform actions, they often demonstrate the acti…
Robotic Imitation of Human Actions
Josua Spisak, Matthias Kerzel, Stefan Wermter
Imitation can allow us to quickly gain an understanding of a new task. Through a demonstration, we can gain direct knowledge about which actions need to be performed and which goal…
CycleIK: Neuro-inspired Inverse Kinematics
Jan-Gerrit Habekost, Erik Strahl, Philipp Allgeuer +2
The paper introduces CycleIK, a neuro-robotic approach that wraps two novel neuro-inspired methods for the inverse kinematics (IK) task, a Generative Adversarial Network (GAN), and…
Clarifying the Half Full or Half Empty Question: Multimodal Container Classification
Josua Spisak, Matthias Kerzel, Stefan Wermter
Multimodal integration is a key component of allowing robots to perceive the world. Multimodality comes with multiple challenges that have to be considered, such as how to integrat…
NICOL: A Neuro-inspired Collaborative Semi-humanoid Robot that Bridges Social Interaction and Reliable Manipulation
Matthias Kerzel, Philipp Allgeuer, Erik Strahl +4
Robotic platforms that can efficiently collaborate with humans in physical tasks constitute a major goal in robotics. However, many existing robotic platforms are either designed f…
Learning Bidirectional Action-Language Translation with Limited Supervision and Incongruent Input
Ozan Özdemir, Matthias Kerzel, Cornelius Weber +4
Human infant learning happens during exploration of the environment, by interaction with objects, and by listening to and repeating utterances casually, which is analogous to unsup…
Learning to Autonomously Reach Objects with NICO and Grow-When-Required Networks
Nima Rahrakhshan, Matthias Kerzel, Philipp Allgeuer +2
The act of reaching for an object is a fundamental yet complex skill for a robotic agent, requiring a high degree of visuomotor control and coordination. In consideration of dynami…
Intelligent problem-solving as integrated hierarchical reinforcement learning
Manfred Eppe, Christian Gumbsch, Matthias Kerzel +3
According to cognitive psychology and related disciplines, the development of complex problem-solving behaviour in biological agents depends on hierarchical cognitive mechanisms. H…
Knowing Earlier what Right Means to You: A Comprehensive VQA Dataset for Grounding Relative Directions via Multi-Task Learning
Kyra Ahrens, Matthias Kerzel, Jae Hee Lee +2
Spatial reasoning poses a particular challenge for intelligent agents and is at the same time a prerequisite for their successful interaction and communication in the physical worl…
Learning Flexible Translation between Robot Actions and Language Descriptions
Ozan Özdemir, Matthias Kerzel, Cornelius Weber +2
Handling various robot action-language translation tasks flexibly is an essential requirement for natural interaction between a robot and a human. Previous approaches require chang…
What is Right for Me is Not Yet Right for You: A Dataset for Grounding Relative Directions via Multi-Task Learning
Jae Hee Lee, Matthias Kerzel, Kyra Ahrens +2
Understanding spatial relations is essential for intelligent agents to act and communicate in the physical world. Relative directions are spatial relations that describe the relati…
Language Model-Based Paired Variational Autoencoders for Robotic Language Learning
Ozan Özdemir, Matthias Kerzel, Cornelius Weber +2
Human infants learn language while interacting with their environment in which their caregivers may describe the objects and actions they perform. Similar to human infants, artific…
A trained humanoid robot can perform human-like crossmodal social attention and conflict resolution
Di Fu, Fares Abawi, Hugo Carneiro +5
To enhance human-robot social interaction, it is essential for robots to process multiple social cues in a complex real-world environment. However, incongruency of input informatio…
Robotic Occlusion Reasoning for Efficient Object Existence Prediction
Mengdi Li, Cornelius Weber, Matthias Kerzel +4
Reasoning about potential occlusions is essential for robots to efficiently predict whether an object exists in an environment. Though existing work shows that a robot with active…