72 citations · 124 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
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,…
From Idea to CAD: A Language Model-Driven Multi-Agent System for Collaborative Design
Felix Ocker, Stefan Menzel, Ahmed Sadik +1
Creating digital models using Computer Aided Design (CAD) is a process that requires in-depth expertise. In industrial product development, this process typically involves entire t…
Tulip Agent -- Enabling LLM-Based Agents to Solve Tasks Using Large Tool Libraries
Felix Ocker, Daniel Tanneberg, Julian Eggert +1
We introduce tulip agent, an architecture for autonomous LLM-based agents with Create, Read, Update, and Delete access to a tool library containing a potentially large number of to…
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…
LaMI: Large Language Models for Multi-Modal Human-Robot Interaction
Chao Wang, Stephan Hasler, Daniel Tanneberg +5
This paper presents an innovative large language model (LLM)-based robotic system for enhancing multi-modal human-robot interaction (HRI). Traditional HRI systems relied on complex…
Exploring Large Language Models as a Source of Common-Sense Knowledge for Robots
Felix Ocker, Jörg Deigmöller, Julian Eggert
Service robots need common-sense knowledge to help humans in everyday situations as it enables them to understand the context of their actions. However, approaches that use ontolog…
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…