4 citations · 7 across the 12 of their papers we have counts for
15 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…
StateVLM: A State-Aware Vision-Language Model for Robotic Affordance Reasoning
Xiaowen Sun, Matthias Kerzel, Mengdi Li +3
Vision-language models have demonstrated strong performance across robotic perception and instruction-following tasks. However, they still struggle with precise spatial reasoning,…
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…
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…
Personalised Explanations in Long-term Human-Robot Interactions
Ferran Gebellí, Anaís Garrell, Jan-Gerrit Habekost +3
In the field of Human-Robot Interaction (HRI), a fundamental challenge is to facilitate human understanding of robots. The emerging domain of eXplainable HRI (XHRI) investigates me…
Curriculum-RLAIF: Curriculum Alignment with Reinforcement Learning from AI Feedback
Jiaye Lin, Mengdi Li, Xufeng Zhao +4
Reward models trained through Reinforcement Learning from AI Feedback (RLAIF) methods frequently suffer from limited generalizability, which hinders the alignment performance of po…
A computational model of infant sensorimotor exploration in the mobile paradigm
Josua Spisak, Sergiu Tcaci Popescu, Stefan Wermter +2
We present a computational model of the mechanisms that may determine infant behavior in the "mobile paradigm". This paradigm has been used in developmental psychology to explore h…
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…
A Framework for Adapting Human-Robot Interaction to Diverse User Groups
Theresa Pekarek Rosin, Vanessa Hassouna, Xiaowen Sun +4
To facilitate natural and intuitive interactions with diverse user groups in real-world settings, social robots must be capable of addressing the varying requirements and expectati…
Mental Modeling of Reinforcement Learning Agents by Language Models
Wenhao Lu, Xufeng Zhao, Josua Spisak +2
Can emergent language models faithfully model the intelligence of decision-making agents? Though modern language models exhibit already some reasoning ability, and theoretically ca…
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…
Bring the Noise: Introducing Noise Robustness to Pretrained Automatic Speech Recognition
Patrick Eickhoff, Matthias Möller, Theresa Pekarek Rosin +2
In recent research, in the domain of speech processing, large End-to-End (E2E) systems for Automatic Speech Recognition (ASR) have reported state-of-the-art performance on various…