2 citations · 6 across the 15 of their papers we have counts for
4 papers · 1 filter
Affordance-based Robot Manipulation with Flow Matching
Fan Zhang, Michael Gienger
We present a framework for assistive robot manipulation, which focuses on two fundamental challenges: first, efficiently adapting large-scale models to downstream scene affordance…
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…
Efficient Symbolic Planning with Views
Stephan Hasler, Daniel Tanneberg, Michael Gienger
Robotic planning systems model spatial relations in detail as these are needed for manipulation tasks. In contrast to this, other physical attributes of objects and the effect of d…
Generating consistent PDDL domains with Large Language Models
Pavel Smirnov, Frank Joublin, Antonello Ceravola +1
Large Language Models (LLMs) are capable of transforming natural language domain descriptions into plausibly looking PDDL markup. However, ensuring that actions are consistent with…