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Jan Leusmann, Steeven Villa Salazar, Chao Wang, Sven Mayer, "Developing and Validating the Perceived System Curiosity Scale (PSC): Measuring Users’ Perceived Curiosity of Systems", CHI Conference on Human Factors in Computing Systems (CHI ’25), 2025.
AbstractLike humans, today's systems, such as robots and voice assistants, can express curiosity to learn and engage with their surroundings. While curiosity is a well-established human trait that enhances social connections and drives learning, no existing scales assess the perceived curiosity of systems. Thus, we introduce the Perceived System Curiosity (PSC) scale to determine how users perceive curious systems. We followed a standardized process of d...
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Lukas Hindemith, Anna-Lisa Vollmer, Christiane Wiebel, Heiko Wersing, Britta Wrede, "Improving HRI through robot architecture transparency", International Journal of Social Robotics, 2025.
AbstractOne ongoing challenge in human-robot interaction design is minimizing user misunderstandings and confusion. While engineers constantly improve the reliability of robots, the user’s mental model about robots and their limitations have to be addressed as well. In this work, we investigate ways to improve the human understanding about robots. For this, we propose FAMILIAR – FunctionAl user Mental model by Increased LegIbility ARchitecture, a tra...
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Andreas Neofytou, Thiago de Jesus de Araujo Rios, Mariusz Bujny, Stefan Menzel, Hyunsun Alicia Kim, "Automatic differentiation-based level set topology optimization for noise minimization in 3D domains considering acoustic-structure interaction", Structural and Multidisciplinary Optimization, 2025.
AbstractThe reduction of vehicle interior noise is one of the important considerations in vehicle design and has become an active research topic in recent years. In this paper, we propose a modularized level set topology optimization (mLSTO) methodology to address noise minimization. One of the main contributions of this work is to allow for more design freedom of the vehicle body compared to previous works in which only size parameters of the vehicle pa...
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Christoph Bergmeir, Frits de Nijs, Evgenii Genov, Abishek Sriramulu, Mahdi Abolghasemi, Richard Bean, John Betts, Quang Bui, Nam Trong Dinh, Nils Einecke, Rasul Esmaeilbeigi, Scott Ferraro, Priya Galketiya, Robert Glasgow, Rakshitha Godahewa, Yanfei Kang, Steffen Limmer, Luis Magdalena, Pablo Montero-Manso, Daniel Peralta-Camara, Yogesh Pipada Sunil Kumar, Alejandro Rosales-Perez, Julian Ruddick, Akylas Stratigakos, Peter Stuckey, Guido Tack, Isaac Triguero, Rui Yuan, "Predict+Optimize Problem in Renewable Energy Scheduling", IEEE Access, vol. 13, pp. 60064-60087, 2025.
AbstractAlgorithms that involve both forecasting and optimization are at the core of solutions to many difficult real-world problems, such as in supply chain (inventory optimization), traffic, and in the transition towards carbon-free energy generation in battery/load/production scheduling in sustainable energy systems. Typically, in these scenarios we want to solve an optimization problem that depends on unknown future values, which therefore need to be...
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Felix Ocker, Jörg Deigmöller, Pavel Smirnov, Julian Eggert, "A Grounded Memory System For Smart Personal Assistants", Extended Semantic Web Conference - workshop on LLM-Integrated Knowledge Graph Generation from Text (Text2KG), 2025.
AbstractA wide variety of applications — ranging from cognitive assistants for dementia patients to robotics — demand a robust memory system grounded in reality. With this paper, we propose a memory system consisting of three components. First, we combine Vision Language Models for image captioning and entity disambiguation with Language Models for precise entity extraction. Second, a knowledge graph is integrated with a vector store to efficiently m...
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Yew Soon Ong, Jiao Liu, Chin Chun Ooi, Abhishek Gupta, Stefan Menzel, Kalyanmoy Deb, "Special Session on Physics-Informed Evolutionary Learning and Optimization", IEEE Congress on Evolutionary Computation, 2025.
AbstractPhysics, as a foundational framework for describing the natural world, has been pivotal to scientific inquiry throughout human history. Physical information has long been integrated into various research domains, including evolutionary computation. Over the past two decades, such information has frequently been applied in data-driven contexts within evolutionary computing. By utilizing data from classical physics simulators - such as the finite e...
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Christiane Attig, Christiane Wiebel, Thomas Franke, "Balancing Autonomy and Automation: Meaningful User Experience in Smart Charging Agent Interactions", Tagung experimentell arbeitender Psychologen (TEAP), 2025.
AbstractEveryday life is increasingly permeated by interactions between humans and autonomous agents. One example is electric vehicle (EV) drivers using smart charging agents (SCA) based on automated information processing to manage limited interdependent resources (e.g., availability of electrical energy, charging times). These agents must not only manage resources effectively, but also ensure meaningful participation in charging decisions, thereby supp...
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Tuan Vu Pham, Thomas H Weisswange, Marc Hassenzahl, "Impact of Affirmative and Negating Robot Gestures on Perceived Personality, Role, and Contribution of a Human Group Member", ACM Designing Interactive Systems (DIS 2025), 2025.
AbstractThere is an interest in how robots could mediate human groups. We investigate how robot gestures influence the perception of a human member’s personality, role in the group, and contribution. In a vignette study (n=96), participants imagined being part of a group discussion and watched a short video of a group member making an argument. In one condition (affirmation) a robot nodded while the member spoke, in the other it shook it...
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Felix Ocker, Jörg Deigmöller, Pavel Smirnov, Julian Eggert, "A Grounded Memory System For Smart Personal Assistants", arXiv, 2025.
AbstractA wide variety of agentic AI applications – ranging from cognitive assistants for dementia patients to robotics – demand a robust memory system grounded in reality. In this paper, we propose such a memory system consisting of three components. First, we combine Vision Language Models for image captioning and entity disambiguation with Large Language Models for consistent information extraction during perception. Second, the extracted informa...
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Raphael Wenzel and Malte Probst , "Spotting the Unfriendly Robot - Towards better Metrics for Interactions", ICRA 2025 Workshop on Advances in Social Robot Navigation, Planning, HRI, and Beyond., 2025.
AbstractEstablishing standardized metrics for Social Robot Navigation (SRN) algorithms for assessing the quality and social compliance of robot behavior around humans is essential for SRN research. Currently, commonly used evaluation metrics lack the ability to quantify how cooperative an agent behaves in interaction with humans. Concretely, in a simple frontal approach scenario, no metric specifically captures if both agents cooperate or if one agent st...
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