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Judith Dörrenbächer, Tuan Vu Pham, Thomas H Weisswange, Alarith Uhde, Anna Hoch, Marc Hassenzahl , "Mediating Urban Social Encounters – Co-Design of Robotic Street Furniture with Adolescents ", 44th ACM Conference on Human Factors in Computing Systems (CHI 2026), 2026.
AbstractAs social interaction continues to shift into digital spaces, spontaneous encounters in public have become untrained and increasingly challenging – particularly for adolescents. This study explores how robotic street furniture can facilitate and mediate such encounters. In a focus group and a theater-based co-design workshop, fourteen adolescents envisioned and enacted ten speculative concepts that encourage social interaction, such as roaming be...
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Johannes Varga, Harald Korinek, Guenther Raidl, Tobias Rodemann , "Timing of Queries in Interactive Job Scheduling", 20th International Conference on Computer Aided Systems Theory, 2026.
AbstractMotivation and Problem: We consider the Interactive Job Scheduling Problem in which human users, e.g. patients in radiation therapy [2], regularly require access to a limited and high-demand resource, e.g. linear accelerators for the treatment of cancer. To avoid no-shows and frustration of the users, it is important to consider the preferences of the users, in particular the times in which they are available to use the resource. Usually, it is n...
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Tuan Vu Pham, Judith Dörrenbächer, Thomas H Weisswange, Marc Hassenzahl , "Robots are Us: From Acting Social to the Social Becoming of Human Groups", 44th ACM Conference on Human Factors in Computing Systems (CHI 2026): Workshop "Everything Is a Robot (and Nothing Is)", 2026.
AbstractRobots designed to mediate human groups often fall into the solu- tionist trap: they are framed as sociable agents that fix problems such as conflict, disengagement, or lack of coordination. We sug- gest a different way of thinking. Robots should be understood as catalysts and agitators of new group experiences; artifacts whose meaning emerges through how groups position, interpret, and in- teract with them collectively. From this perspecti...
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Malte Probst , Raphael Wenzel, Monica Dasi , "Responsibility and Engagement - Evaluating Interactions in Social Robot Navigation", 2026 IEEE International Conference on Robotics & Automation, 2026.
AbstractIn Social Robot Navigation (SRN), the availability of meaningful metrics is crucial for evaluating trajectories from human-robot interactions. In the SRN context, such interactions often relate to resolving conflicts between two or more agents. Correspondingly, the shares to which agents contribute to the resolution of such conflicts are important. This paper builds on recent work, which proposed a Responsibility metric capturing such shares. We...
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Christiane Attig and Christiane Wiebel , "Beyond Tools: The Perception of AI as a Social Teammate in Human-AI Collaboration", 13. Fachgruppentagung der Fachgruppe Arbeits-, Organisations- und Wirtschaftspsychologie gemeinsam mit der Fachgruppe Ingenieurpsychologie (AOWI 2025), 2025.
AbstractHuman-AI interaction is often framed in terms of task efficiency, but users do not necessarily interact with AI systems as tools. Instead, they may perceive them as social partners with specified roles. The subjective ascription of roles in human-AI teaming can be understood as a multi-factorial, dynamic process, depending on task characteristics, AI functionality, and the user’s perception of the AI and the joint task. Consequently, to predict ...
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Chao Wang, Michael Gienger, Fan Zhang , "Real-Time Robotic Emotional Expression from Mixed-Reality Demonstrations via Flow Matching", IROS 2025 Late-breaking work, 2025.
AbstractExpressive behaviors in robots are critical for effectively conveying their emotional states during interactions with humans. In this work, we present a framework that autonomously generates realistic and diverse robotic emotional expressions based on expert human demonstrations captured in Mixed Reality (MR). Our system enables experts to teleoperate a virtual robot from a first-person perspective, capturing their facial expressions, head moveme...
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Jan Leusmann, Chao Wang, Sven Mayer, Michael Gienger, Albrecht Schmidt , "How to Design Interactive Physical Learning Robots That Are Fun to Teach: If You Are Curious, I Will Show You!", IEEE Pervasive Computing, 2025.
AbstractRecently, we have seen a rise in systems with various levels of autonomy, such as smart environments, robots, and cars. Teaching these systems effectively is crucial for making them useful, enforcing desired behavior, and correcting undesired actions. In-situ learning and adapting to specific contexts (e.g., culture, user type, preferences) are essential for effective real-world learning. Curiosity-driven behavior can lead to more natural interac...
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Jan Leusmann, Anna Belardinelli, Luke Haliburton, Albrecht Schmidt, Stephan Hasler, Sven Mayer, Michael Gienger, Chao Wang , "Investigating LLM-Driven Curiosity in Human-Robot Interaction", CHI conference 2025, 2025.
AbstractIn the future, we need seamless and natural collaboration with robots. Currently, robots can only perform tasks that they have been taught either in the development stage or by using techniques like learning from demonstration. However, for humans, the natural way to learn is often through curiosity. Currently, it is unclear how users perceive the curiosity of robots. To address this, we developed a curious and a non-curious character using a Lar...
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Amirreza Razmjoo, Michael Gienger, Fan Zhang , "CCDP: Composition of Conditional Diffusion Policy for Interactive Sampling Refinement", International Conference on Intelligent Robots and Systems, IROS 2025, 2025.
AbstractLearning from demonstrations offers a promising approach in robotics by enabling systems to learn directly from data without requiring explicit models, simulations, or detailed task definitions. During inference, actions are sampled from the learned distribution and executed on the robot. However, sampled actions may fail for various reasons, and simply repeating the sampling step until a successful action is obtained can be inefficient. In this ...
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Leonard Hinckeldey, Elliot Fosong , Elle Miller, Trevor McInroe, Patricia Wollstadt, Christiane Wiebel, Stefano V. Albrecht , "Assistax: A Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics", Second Coordination and Cooperation in Multi-Agent Reinforcement Learning Workshop CoCoMARL 2025, RLC, 2025.
AbstractThe development of reinforcement learning (RL) algorithms has been largely driven by ambitious challenge tasks and benchmarks. Games have dominated RL benchmarks because they present relevant challenges, are inexpensive to run and easy to understand. While games such as Go and Atari have led to many breakthroughs, they often do not directly translate to real-world embodied applications. In recognising the need to diversify RL benchmarks and addre...
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