activity
20182026
most citedDoing Right by Not Doing Wrong in Human-Robot Collaboration

3 citations · 7 across the 11 of their papers we have counts for

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20 papers · 1 filter

cs.RO2026

Relational Semantic Reasoning on 3D Scene Graphs for Open World Interactive Object Search

Imen Mahdi, Matteo Cassinelli, Fabien Despinoy +2

Open-world interactive object search in household environments requires understanding semantic relationships between objects and their surrounding context to guide exploration effi…

cs.RO2026

Articulated 3D Scene Graphs for Open-World Mobile Manipulation

Martin Büchner, Adrian Röfer, Tim Engelbracht +5

Semantics has enabled 3D scene understanding and affordance-driven object interaction. However, robots operating in real-world environments face a critical limitation: they cannot…

cs.RO2025

DiWA: Diffusion Policy Adaptation with World Models

Akshay L Chandra, Iman Nematollahi, Chenguang Huang +3

Fine-tuning diffusion policies with reinforcement learning (RL) presents significant challenges. The long denoising sequence for each action prediction impedes effective reward pro…

cs.RO2025

MORE: Mobile Manipulation Rearrangement Through Grounded Language Reasoning

Mohammad Mohammadi, Daniel Honerkamp, Martin Büchner +5

Autonomous long-horizon mobile manipulation encompasses a multitude of challenges, including scene dynamics, unexplored areas, and error recovery. Recent works have leveraged found…

cs.RO20242 cited

Task-Driven Co-Design of Mobile Manipulators

Raphael Schneider, Daniel Honerkamp, Tim Welschehold +1

Recent interest in mobile manipulation has resulted in a wide range of new robot designs. A large family of these designs focuses on modular platforms that combine existing mobile…

cs.RO20241 cited

Learning Robotic Manipulation Policies from Point Clouds with Conditional Flow Matching

Eugenio Chisari, Nick Heppert, Max Argus +3

Learning from expert demonstrations is a promising approach for training robotic manipulation policies from limited data. However, imitation learning algorithms require a number of…