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Chao Wang, Michael Gienger, Fan Zhang , "Autonomous Generation of Real-time Robotic Emotional Expressions via Human Demonstration in Mixed Reality", 34th IEEE International Conference on Robot and Human Interactive Communication, 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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Anna Belardinelli, Chao Wang, Daniel Tanneberg, Stephan Hasler, Michael Gienger , "Train your robot in AR: insights and challenges for humans and robots in continual teaching and learning", Frontiers in Robotics and AI, 2025.
AbstractSupportive robots that can be deployed in our homes will need to be understandable, operable, and teachable by non-expert users. This calls for an intuitive Human-Robot Interaction approach that is also safe and sustainable in the long term. Still, few studies have looked at repeated, unscripted interactions in loosely supervised settings, with a robot incrementally learning from the user and consequentially expanding its knowledge and abilities....
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Derck Hong Da Chu and Chao Wang , "ARive: Assisting Drivers with In-Car Augmented Reality for Risk Zone Detection", Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies , 2025.
AbstractUrban driving demands rapid decision-making, often hampered by human errors such as distraction and fatigue, risking safety and efficiency. A novel solution proposes using augmented reality (AR) to mitigate these risks by projecting dynamic risk zones around vehicles and pedestrians, directly into the driver's field of vision. This system aims to enhance driver awareness and promote defensive driving by visually indicating the movement of nearby ...
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Tobias Rodemann , "Future Roadmap für das Mechatronische Engineering Systems Engineering - Hinweise aus der aktuellen Forschungslandschaft", HS Aalen, 2025.
AbstractTalk at the HS Aalen on 13 January 2025 within the Mechatronics Seminar (in German)...
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Muhammad Ashfaq, Ahmed Sadik, Tommi Mikkonen, Muhammad Waseem, Niko Mäkitalo , "PrePrint - LLM-Enhanced Holonic Architecture for Self-Adaptive System of Systems", arXiv, 2025.
AbstractAs modern system of systems (SoS) become increasingly adaptive and human-centred, traditional architectures often struggle to support interoperability, reconfigurability, and effective human-system interaction. This paper addresses these challenges by advancing the state-of-the-art holonic architecture for SoS, offering two main contributions to support these adaptive needs. First, we propose a layered architecture for holons, which includes reas...
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Ebubechukwu Ike, Johane Takeuchi, Antonello Ceravola, Frank Joublin , "Automating Dialogue Evaluation: Large Language Mode versus Human Judgement", HCI International 2025, 2025.
AbstractAs dialogue systems and chatbots become more common in daily life, efficient and accurate evaluation methods are crucial. This study compares human and AI assessments across various dialogue scenarios, focusing on seven key performance indicators (KPIs): Coherence, Innovation, Concreteness, Goal Contribution, Commonsense Contradiction, Incorrect Fact, and Redundancy. Using the GPT-4o API, we generated diverse conversation datasets and conducted a...
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Tobias Rodemann and Christiane Attig , "Real Application Challenges in Evolutionary Optimization? People!", EvoApplications2025, pp. 469-481, 2025.
AbstractThe application of evolutionary optimization methods for real world problems is often far less straight-forward than expected. One of the main challenges are the involved people in real businesses that decide on whether optimization projects are successful or not. In this work we present a few insights from 20+ years of applying EAs (mostly multi- and many-objective) with in-house customers and point to some key psychological insights that can ex...
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Ahmed Sadik, Muhammad Ashfaq, Niko Mäkitalo, Tommi Mikkonen , "Human-LLM Synergy in Context-Aware Adaptive Architecture for Scalable Drone Swarm Operation", arXiv, 2025.
AbstractThe deployment of autonomous drone swarms in disaster response missions necessitates the development of flexible, scalable, and robust coordination systems. Traditional fixed architectures struggle to cope with dynamic and unpredictable environments, leading to inefficiencies in energy consumption and connectivity. This paper addresses this gap by proposing an adaptive architecture for drone swarms, leveraging a Large Language Model (LLM) to dyna...
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Felix Ocker , "LLM-based agents in robotics", Ringvorlesung an der TUM "Digitaler Zwilling im Engineering und Design", 2025.
AbstractLLM-based agents in robotics...
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Kyle Poland , "A Measure-Theoretic Perspective on Multivariate Information with Applications to Data Science", Georg-August-Universität Göttingen, 2024.
AbstractDescribing statistical dependencies is foundational to empirical scientific research. For uncovering intricate and possibly nonlinear dependencies between a single target variable and several source variables within a system, a principled and versatile framework can be found in the theory of partial information decomposition (PID). Despite PID conceptually being defined for any type of random variables, so far, PID could only be quantified for ...
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