27 citations · 42 across the 31 of their papers we have counts for
33 papers
RoboFind: Multi-Agent Personalized Object Search for People Who Are Blind or Have Low Vision
Ruiping Liu, Shaofang Quan, Qian Yin +10
Blind and low-vision users often need to locate a specific personal object rather than an arbitrary instance of the same category. The task calls for a robot that can move through…
Depth-Wise Probing and Pruning of the Planning Token in a Driving Vision-Language-Action Model
Harisankar Babu, Benjamin Coors, Christopher Lang +3
Vision-language-action (VLA) models route driving decisions through a deep language model, but it is unclear how much of that depth the action itself requires. We study a represent…
Learning to Forget -- Hierarchical Episodic Memory for Lifelong Robot Deployment
Leonard Bärmann, Joana Plewnia, Alex Waibel +1
Robots must verbalize their past experiences when users ask "Where did you put my keys?" or "Why did the task fail?" Yet maintaining life-long episodic memory (EM) from continuous…
Unified Learning of Temporal Task Structure and Action Timing for Bimanual Robot Manipulation
Christian Dreher, Patrick Dormanns, Andre Meixner +1
Bimanual manipulation requires both temporal task structure - which actions precede or overlap others - and concrete timing - when each action starts and how long it takes. Symboli…
ManipulationNet: An Infrastructure for Benchmarking Real-World Robot Manipulation with Physical Skill Challenges and Embodied Multimodal Reasoning
Yiting Chen, Kenneth Kimble, Edward H. Adelson +20
Dexterous manipulation enables robots to purposefully alter the physical world, transforming them from passive observers into active agents in unstructured environments. This capab…
Intuitive Programming, Adaptive Task Planning, and Dynamic Role Allocation in Human-Robot Collaboration
Marta Lagomarsino, Elena Merlo, Andrea Pupa +5
Remarkable capabilities have been achieved by robotics and AI, mastering complex tasks and environments. Yet, humans often remain passive observers, fascinated but uncertain how to…
Contact Wasserstein Geodesics for Non-Conservative Schrödinger Bridges
Andrea Testa, Søren Hauberg, Tamim Asfour +1
The Schrödinger Bridge provides a principled framework for modeling stochastic processes between distributions; however, existing methods are limited by energy-conservation assumpt…
Taxonomy-aware Dynamic Motion Generation on Hyperbolic Manifolds
Luis Augenstein, Noémie Jaquier, Tamim Asfour +1
Human-like motion generation for robots often draws inspiration from biomechanical studies, which often categorize complex human motions into hierarchical taxonomies. While these t…
Diffusion-Based Impedance Learning for Contact-Rich Manipulation Tasks
Noah Geiger, Tamim Asfour, Neville Hogan +1
Learning-based methods excel at robot motion generation but remain limited in contact-rich physical interaction. Impedance control provides stable and safe contact behavior but req…
MoRe-ERL: Learning Motion Residuals using Episodic Reinforcement Learning
Xi Huang, Hongyi Zhou, Ge Li +5
We propose MoRe-ERL, a framework that combines Episodic Reinforcement Learning (ERL) and residual learning, which refines preplanned reference trajectories into safe, feasible, and…
CLEVER: Stream-based Active Learning for Robust Semantic Perception from Human Instructions
Jongseok Lee, Timo Birr, Rudolph Triebel +1
We propose CLEVER, an active learning system for robust semantic perception with Deep Neural Networks (DNNs). For data arriving in streams, our system seeks human support when enco…
Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning
Harisankar Babu, Philipp Schillinger, Tamim Asfour
We introduce TAPAS (Task-based Adaptation and Planning using AgentS), a multi-agent framework that integrates Large Language Models (LLMs) with symbolic planning to solve complex t…
Geometric Contact Flows: Contactomorphisms for Dynamics and Control
Andrea Testa, Søren Hauberg, Tamim Asfour +1
Accurately modeling and predicting complex dynamical systems, particularly those involving force exchange and dissipation, is crucial for applications ranging from fluid dynamics t…
Learning Spatial Bimanual Action Models Based on Affordance Regions and Human Demonstrations
Björn S. Plonka, Christian Dreher, Andre Meixner +2
In this paper, we present a novel approach for learning bimanual manipulation actions from human demonstration by extracting spatial constraints between affordance regions, termed…
Safe Reinforcement Learning of Robot Trajectories in the Presence of Moving Obstacles
Jonas Kiemel, Ludovic Righetti, Torsten Kröger +1
In this paper, we present an approach for learning collision-free robot trajectories in the presence of moving obstacles. As a first step, we train a backup policy to generate evas…
On Probabilistic Pullback Metrics for Latent Hyperbolic Manifolds
Luis Augenstein, Noémie Jaquier, Tamim Asfour +1
Probabilistic Latent Variable Models (LVMs) excel at modeling complex, high-dimensional data through lower-dimensional representations. Recent advances show that equipping these la…
A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics
Katharina Friedl, Noémie Jaquier, Jens Lundell +2
By incorporating physical consistency as inductive bias, deep neural networks display increased generalization capabilities and data efficiency in learning nonlinear dynamic models…
Episodic Memory Verbalization using Hierarchical Representations of Life-Long Robot Experience
Leonard Bärmann, Chad DeChant, Joana Plewnia +4
Verbalization of robot experience, i.e., summarization of and question answering about a robot's past, is a crucial ability for improving human-robot interaction. Previous works ap…
Force Myography based Torque Estimation in Human Knee and Ankle Joints
Charlotte Marquardt, Arne Schulz, Miha Dezman +3
The online adaptation of exoskeleton control based on muscle activity sensing offers a promising approach to personalizing exoskeleton behavior based on the user's biosignals. Whil…
PerAct2: Benchmarking and Learning for Robotic Bimanual Manipulation Tasks
Markus Grotz, Mohit Shridhar, Tamim Asfour +1
Bimanual manipulation is challenging due to precise spatial and temporal coordination required between two arms. While there exist several real-world bimanual systems, there is a l…
Influence of Motion Restrictions in an Ankle Exoskeleton on Gait Kinematics and Stability in Straight Walking
Miha Dezman, Charlotte Marquardt, Adnan Ugur +1
Exoskeleton devices impose kinematic constraints on a user's motion and affect their stability due to added mass but also due to the simplified mechanical design. This paper invest…
SciEx: Benchmarking Large Language Models on Scientific Exams with Human Expert Grading and Automatic Grading
Tu Anh Dinh, Carlos Mullov, Leonard Bärmann +15
With the rapid development of Large Language Models (LLMs), it is crucial to have benchmarks which can evaluate the ability of LLMs on different domains. One common use of LLMs is…
Bi-KVIL: Keypoints-based Visual Imitation Learning of Bimanual Manipulation Tasks
Jianfeng Gao, Xiaoshu Jin, Franziska Krebs +2
Visual imitation learning has achieved impressive progress in learning unimanual manipulation tasks from a small set of visual observations, thanks to the latest advances in comput…
Visual Imitation Learning of Task-Oriented Object Grasping and Rearrangement
Yichen Cai, Jianfeng Gao, Christoph Pohl +1
Task-oriented object grasping and rearrangement are critical skills for robots to accomplish different real-world manipulation tasks. However, they remain challenging due to partia…