collaborators

7 papers

cs.AI2026

Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challenges

Vincent Henkel, Felix Gehlhoff, David Kube +13

Foundation models, particularly large language models, are increasingly integrated into agent architectures for industrial tasks such as decision support, process monitoring, and e…

cs.RO2026

MERGE: Guided Vision-Language Models for Multi-Actor Event Reasoning and Grounding in Human-Robot Interaction

Joerg Deigmoeller, Nakul Agarwal, Stephan Hasler +8

We introduce MERGE, a system for situational grounding of actors, objects, and events in dynamic human-robot group interactions. Effective collaboration in such settings requires c…

cs.RO2025

CARMA: Context-Aware Situational Grounding of Human-Robot Group Interactions by Combining Vision-Language Models with Object and Action Recognition

Joerg Deigmoeller, Stephan Hasler, Nakul Agarwal +8

We introduce CARMA, a system for situational grounding in human-robot group interactions. Effective collaboration in such group settings requires situational awareness based on a c…

cs.AI2025

A Grounded Memory System For Smart Personal Assistants

Felix Ocker, Jörg Deigmöller, Pavel Smirnov +1

A wide variety of agentic AI applications - ranging from cognitive assistants for dementia patients to robotics - demand a robust memory system grounded in reality. In this paper,…

cs.RO2025

To Help or Not to Help: LLM-based Attentive Support for Human-Robot Group Interactions

Daniel Tanneberg, Felix Ocker, Stephan Hasler +6

How can a robot provide unobtrusive physical support within a group of humans? We present Attentive Support, a novel interaction concept for robots to support a group of humans. It…

cs.RO2025

CoPAL: Corrective Planning of Robot Actions with Large Language Models

Frank Joublin, Antonello Ceravola, Pavel Smirnov +7

In the pursuit of fully autonomous robotic systems capable of taking over tasks traditionally performed by humans, the complexity of open-world environments poses a considerable ch…