2 citations · 3 across the 16 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
Leveraging Vision-Language Models for Open-Vocabulary Instance Segmentation and Tracking
Bastian Pätzold, Jan Nogga, Sven Behnke
Vision-language models (VLMs) excel in visual understanding but often lack reliable grounding capabilities and actionable inference rates. Integrating them with open-vocabulary obj…
LIAM: Multimodal Transformer for Language Instructions, Images, Actions and Semantic Maps
Yihao Wang, Raphael Memmesheimer, Sven Behnke
The availability of large language models and open-vocabulary object perception methods enables more flexibility for domestic service robots. The large variability of domestic task…