1 citations · 1 across the 7 of their papers we have counts for
4 papers · 1 filter
MamMA: A Mamba-Based Pedestrian Trajectory Prediction Algorithm Considering Occupancy Map and Pedestrian Awareness States
Juncen Long, Xiaofeng Jin, Gianluca Bardaro +2
Many pedestrian trajectory prediction algorithms have been proposed to improve the safety of navigation for mobile robots working in human-robot coexistence environments. Some pede…
Act, Think or Abstain: Complexity-Aware Adaptive Inference for Vision-Language-Action Models
Riccardo Andrea Izzo, Gianluca Bardaro, Matteo Matteucci
Current research on Vision-Language-Action (VLA) models predominantly focuses on enhancing generalization through reasoning techniques. While effective, these improvements increase…
Improving Robustness of Vision-Language-Action Models by Restoring Corrupted Visual Inputs
Daniel Yezid Guarnizo Orjuela, Leonardo Scappatura, Veronica Di Gennaro +3
Vision-Language-Action (VLA) models have emerged as a dominant paradigm for generalist robotic manipulation, unifying perception and control within a single end-to-end architecture…
A Spatio-temporal Graph Network Allowing Incomplete Trajectory Input for Pedestrian Trajectory Prediction
Juncen Long, Gianluca Bardaro, Simone Mentasti +1
Pedestrian trajectory prediction is important in the research of mobile robot navigation in environments with pedestrians. Most pedestrian trajectory prediction algorithms require…