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Elisabeth Menendez, Santiago Martinez, Carlos Balaguer, Michael Gienger, Anna Belardinelli , "SemanticScanpath: Combining Gaze and Speech for Situated Human-Robot Interaction Using LLMs", arxiv, 2025.
AbstractLarge Language Models (LLMs) have substan- tially improved the conversational capabilities of social robots. Nevertheless, for an intuitive and fluent human-robot inter- action, robots should be able to ground the conversation by relating ambiguous or underspecified spoken utterances to the current physical situation and to the intents expressed non verbally by the user, for example by using referential gaze. Here we propose a representati...
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Felix Ocker and Julian Eggert , "Connecting the Dots: Retrieval-Augmented Generation with Graphs", Honda Data Days, 2025.
AbstractAn overview of GraphRAG and its applications for cognitive assistants and technical documents....
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Daniel Tanneberg , "Local Pairwise Distance Matching for Backpropagation-Free Reinforcement Learning", European Conference on Artificial Intelligence, 2025.
AbstractTraining neural networks with reinforcement learning (RL) typically relies on backpropagation (BP), necessitating storage of activations from the forward pass for subsequent backward updates. Furthermore, backpropagating error signals through multiple layers often leads to vanishing or exploding gradients, which can degrade learning performance and stability. We propose a novel approach that trains each layer of the neural network using local si...
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Thomas H Weisswange, Hifza Javed, Manuel Dietrich, Malte F. Jung, Nawid Jamali , "Design Implications for Robots that Facilitate Groups - A Scoping Review on Improving Group Interactions through Directed Robot Action", ACM Transactions on Human-Robot Interaction, 2025.
AbstractMany human activities are performed in groups---making decisions in workplace meetings, cooperating on a sports team, or meeting with friends for dinner. All these activities involve complex conditions and interaction processes that influence their outcomes in terms of performance, personal goals, and group objectives. As robots are increasingly being positioned within groups, improving these outcomes has emerged as an important application area ...
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Leon Keller, Daniel Tanneberg, Jan Peters , "Neuro-Symbolic Imitation Learning: Discovering Symbolic Abstractions for Skill Learning", IEEE International Conference on Robotics and Automation (ICRA), 2025.
AbstractImitation learning is a popular method for teaching robots new behaviors. However, most existing methods focus on teaching short, isolated skills rather than long, multi-step tasks. To bridge this gap, imitation learning algorithms must not only learn individual skills but also an abstract understanding of how to sequence these skill to perform extended tasks effectively. This paper addresses this challenge by proposing a neuro-symbolic imitatio...
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Markus Amann, Thomas H Weisswange, Malte Probst , Stina Larsson, Maytheewat Aramrattana, Anna Sjörs Dahlman, Miguel Ángel Sotelo , "Coordinating Internal and External HMIs for Cooperative Driver-Pedestrian Situation Resolution [Poster]", Human Factors Summer School 2025, 2025.
AbstractTraffic interactions between vehicles and pedestrians are inherently uncertain due to the dynamic nature of the interaction partners’ behavior and situational ambiguity. The exchange of information between drivers and other road users could improve mutual understanding of the situation and planned behavior. Existing products and research approaches aim at enhancing mutual understanding by providing information through internal or external human-m...
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Simon Manschitz, Berk Güler, Wei Ma, Dirk Ruiken , "Sampling-Based Grasp and Collision Prediction for Assisted Teleoperation", International Conference on Robotics and Automation (ICRA), 2025.
AbstractShared autonomy allows for combining the global planning capabilities of a human operator with the strengths of a robot such as repeatability and accurate control. In a real-time teleoperation setting, one possibility for shared control is to let the human operator decide for the rough movement and to let the robot do fine adjustments, e.g., when the view of the operator is occluded. We present a learning-based concept for shared autonomy that ai...
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Berk Güler, Simon Manschitz, Kay Pompetzki, Jan Peters , "Towards Assistive Teleoperation for Knot Untangling", 1st German Robotics Conference, 2025.
AbstractManipulating deformable linear objects (DLOs) such as ropes is challenging due to their complex dynamics. To address these issues, we present a novel assistive teleoperation framework that combines human expertise with autonomous assistance. Our approach integrates a vision-based module to identify grasp poses, a shared autonomy mechanism that balances human input with autonomous guidance, and an optimization-based inverse kinematic solver for sm...
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Simon Kohaut, Felix Divo, Benedict Flade, Devendra Dhami, Julian Eggert, Kristian Kersting , "The Constitutional Filter: Bayesian Estimation of Compliant Agents", IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3092-3099, 2025.
AbstractPredicting agents impacted by legal policies, physical limitations, and operational preferences is inherently difficult. In recent years, neuro-symbolic methods have emerged, integrating machine learning and symbolic reasoning models into end-to-end learnable systems. Hereby, a promising avenue for expressing high-level constraints over multi-modal input data in robotics has opened up. This work introduces an approach for Bayesian estimation of a...
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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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