6 papers
AnchorD: Metric Grounding of Monocular Depth Using Factor Graphs
Simon Dorer, Martin Büchner, Nick Heppert +1
Dense and accurate depth estimation is essential for robotic manipulation, grasping, and navigation, yet currently available depth sensors are prone to errors on transparent, specu…
Hoi! - A Multimodal Dataset for Force-Grounded, Cross-View Articulated Manipulation
Tim Engelbracht, René Zurbrügg, Matteo Wohlrapp +5
We present a dataset for force-grounded, cross-view articulated manipulation that couples what is seen with what is done and what is felt during real human interaction. The dataset…
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…
OpenLex3D: A Tiered Evaluation Benchmark for Open-Vocabulary 3D Scene Representations
Christina Kassab, Sacha Morin, Martin Büchner +5
3D scene understanding has been transformed by open-vocabulary language models that enable interaction via natural language. However, at present the evaluation of these representat…
Visual Loop Closure Detection Through Deep Graph Consensus
Martin Büchner, Liza Dahiya, Simon Dorer +4
Visual loop closure detection traditionally relies on place recognition methods to retrieve candidate loops that are validated using computationally expensive RANSAC-based geometri…
Collaborative Dynamic 3D Scene Graphs for Open-Vocabulary Urban Scene Understanding
Tim Steinke, Martin Büchner, Niclas Vödisch +1
Mapping and scene representation are fundamental to reliable planning and navigation in mobile robots. While purely geometric maps using voxel grids allow for general navigation, o…