84 citations · 288 across the 30 of their papers we have counts for
7 papers · 1 filter
Visual Perception Engine: Fast and Flexible Multi-Head Inference for Robotic Vision Tasks
Jakub Łucki, Jonathan Becktor, Georgios Georgakis +2
Deploying multiple machine learning models on resource-constrained robotic platforms for different perception tasks often results in redundant computations, large memory footprints…
Pixels-to-Graph: Real-time Integration of Building Information Models and Scene Graphs for Semantic-Geometric Human-Robot Understanding
Antonello Longo, Chanyoung Chung, Matteo Palieri +4
Autonomous robots are increasingly playing key roles as support platforms for human operators in high-risk, dangerous applications. To accomplish challenging tasks, an efficient hu…
Risk-Guided Diffusion: Toward Deploying Robot Foundation Models in Space, Where Failure Is Not An Option
Rohan Thakker, Adarsh Patnaik, Vince Kurtz +10
Safe, reliable navigation in extreme, unfamiliar terrain is required for future robotic space exploration missions. Recent generative-AI methods learn semantically aware navigation…
General-Purpose Robotic Navigation via LVLM-Orchestrated Perception, Reasoning, and Acting
Bernard Lange, Anil Yildiz, Mansur Arief +3
Developing general-purpose navigation policies for unknown environments remains a core challenge in robotics. Most existing systems rely on task-specific neural networks and fixed…
CompSLAM: Complementary Hierarchical Multi-Modal Localization and Mapping for Robot Autonomy in Underground Environments
Shehryar Khattak, Timon Homberger, Lukas Bernreiter +5
Robot autonomy in unknown, GPS-denied, and complex underground environments requires real-time, robust, and accurate onboard pose estimation and mapping for reliable operations. Th…
Holistic Fusion: Task- and Setup-Agnostic Robot Localization and State Estimation with Factor Graphs
Julian Nubert, Turcan Tuna, Jonas Frey +4
Seamless operation of mobile robots in challenging environments requires low-latency local motion estimation and accurate global localization. While most sensor-fusion approaches a…