RoboCup@Home 2024 OPL Winner NimbRo: Anthropomorphic Service Robots using Foundation Models for Perception and Planning
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Abstract (arXiv)
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 describe our hardware setup and give an overview of the results for the task stages and the final demonstration. For this year's competition, we put a special emphasis on open-vocabulary object segmentation and grasping approaches that overcome the labeling overhead of supervised vision approaches, commonly used in RoboCup@Home. We successfully demonstrated that we can segment and grasp non-labeled objects by text descriptions. Further, we extensively employed LLMs for natural language understanding and task planning. Throughout the competition, our approaches showed robustness and generalization capabilities. A video of our performance can be found online.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 19 Dec 2024.
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Citing papers per year: 2025: 2; 2026: 2.
4 papers.
- 2025Leveraging Vision-Language Models for Open-Vocabulary Instance Segmentation and Trackingcited by 4
- 2025EL3DD: Extended Latent 3D Diffusion for Language Conditioned Multitask Manipulationcited by 0
- 2026CAD-Prompted SAM3: Geometry-Conditioned Instance Segmentation for Industrial Objectscited by 0
- 2026Efficient Image Annotation via Semi-Supervised Object Segmentation with Label Propagationcited by 0
- 2026Efficient Image Annotation via Semi-Supervised Object Segmentation with Label Propagation24 Apr 2026
- 2026CAD-Prompted SAM3: Geometry-Conditioned Instance Segmentation for Industrial Objects24 Feb 2026
- 2025EL3DD: Extended Latent 3D Diffusion for Language Conditioned Multitask Manipulation17 Nov 2025
- 2025Leveraging Vision-Language Models for Open-Vocabulary Instance Segmentation and Tracking18 Mar 2025