16 citations · 21 across the 8 of their papers we have counts for
6 papers · 1 filter
What do VLM-Based Vision-Language Navigation Models Rely on: Interpreting and Steering Policy Behavior
Débora Oliveira Makowski, Samiran Gode, Abhijeet Nayak +4
Modern Vision-Language Navigation (VLN) models rely mostly on pre-trained large Vision-Language Models (VLMs) to predict navigation actions. While this fusion of language instructi…
Probabilistic Scene Graphs: Hierarchical Representation and Real-time System
Waqas Ali, Michele Antonazzi, Timon Homberger +4
3D scene graphs provide semantically rich and hierarchical representations for robot perception. However, existing systems do not maintain uncertainty as an explicit belief or prop…
3D Scene Graphs: Open Challenges and Future Directions
Dennis Rotondi, Francesco Argenziano, Sebastian Koch +10
3D Scene Graphs (3DSGs) have emerged as a powerful representation for spatial AI by combining geometric grounding with semantic and relational abstractions of the environment. Thei…
Long-Term Human Trajectory Prediction using 3D Dynamic Scene Graphs
Nicolas Gorlo, Lukas Schmid, Luca Carlone
We present a novel approach for long-term human trajectory prediction in indoor human-centric environments, which is essential for long-horizon robot planning in these environments…
Clio: Real-time Task-Driven Open-Set 3D Scene Graphs
Dominic Maggio, Yun Chang, Nathan Hughes +6
Modern tools for class-agnostic image segmentation (e.g., SegmentAnything) and open-set semantic understanding (e.g., CLIP) provide unprecedented opportunities for robot perception…
Khronos: A Unified Approach for Spatio-Temporal Metric-Semantic SLAM in Dynamic Environments
Lukas Schmid, Marcus Abate, Yun Chang +1
Perceiving and understanding highly dynamic and changing environments is a crucial capability for robot autonomy. While large strides have been made towards developing dynamic SLAM…