2 papers
cs.RO2026
SIL: Symbiotic Interactive Learning for Language-Conditioned Human-Agent Co-Adaptation
Linus Nwankwo, Bjoern Ellensohn, Christian Rauch +1
Today's autonomous agents, largely driven by foundation models (FMs), can understand natural language instructions and solve long-horizon tasks with human-like reasoning. However,…
cs.RO2025
Real-Time 3D Vision-Language Embedding Mapping
Christian Rauch, Björn Ellensohn, Linus Nwankwo +2
A metric-accurate semantic 3D representation is essential for many robotic tasks. This work proposes a simple, yet powerful, way to integrate the 2D embeddings of a Vision-Language…