27 citations · 42 across the 31 of their papers we have counts for
8 papers · 1 filter
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…