activity
20242026
most citedLeveraging Vision-Language Models for Open-Vocabulary Instance Segmentation and Tracking

2 citations · 3 across the 13 of their papers we have counts for

collaborators
Showing cs.ROShow all

7 papers · 1 filter

cs.RO2026

ContactFlow: A video action conditioning that transfers across embodiments

Sami Azirar, Enrico Pallotta, Jan Nogga +3

World models offer a promising route toward robot planning by enabling agents to imagine and verify the consequences of actions before execution. However, current video-based world…

cs.RO2025

OMCL: Open-vocabulary Monte Carlo Localization

Evgenii Kruzhkov, Raphael Memmesheimer, Sven Behnke

Robust robot localization is an important prerequisite for navigation, but it becomes challenging when the map and robot measurements are obtained from different sensors. Prior met…

cs.RO2025

EL3DD: Extended Latent 3D Diffusion for Language Conditioned Multitask Manipulation

Jonas Bode, Raphael Memmesheimer, Sven Behnke

Acting in human environments is a crucial capability for general-purpose robots, necessitating a robust understanding of natural language and its application to physical tasks. Thi…

cs.RO2025

Integration of the TIAGo Robot into Isaac Sim with Mecanum Drive Modeling and Learned S-Curve Velocity Profiles

Vincent Schoenbach, Marvin Wiedemann, Raphael Memmesheimer +2

Efficient physics simulation has significantly accelerated research progress in robotics applications such as grasping and assembly. The advent of GPU-accelerated simulation framew…

cs.RO20241 cited

RoboCup@Home 2024 OPL Winner NimbRo: Anthropomorphic Service Robots using Foundation Models for Perception and Planning

Raphael Memmesheimer, Jan Nogga, Bastian Pätzold +8

We present the approaches and contributions of the winning team NimbRo@Home at the RoboCup@Home 2024 competition in the Open Platform League held in Eindhoven, NL. Further, we desc…

cs.RO2024

A Comparison of Prompt Engineering Techniques for Task Planning and Execution in Service Robotics

Jonas Bode, Bastian Pätzold, Raphael Memmesheimer +1

Recent advances in LLM have been instrumental in autonomous robot control and human-robot interaction by leveraging their vast general knowledge and capabilities to understand and…