6 papers
Multimodal Behavior Tree Generation: A Small Vision-Language Model for Robot Task Planning
Cristiano Battistini, Riccardo Andrea Izzo, Gianluca Bardaro +1
Large and small language models have been widely used for robotic task planning. At the same time, vision-language models (VLMs) have successfully tackled problems such as image ca…
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…
BTGenBot-2: Efficient Behavior Tree Generation with Small Language Models
Riccardo Andrea Izzo, Gianluca Bardaro, Matteo Matteucci
Recent advances in robot learning increasingly rely on LLM-based task planning, leveraging their ability to bridge natural language with executable actions. While prior works showc…
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…
BTGenBot: Behavior Tree Generation for Robotic Tasks with Lightweight LLMs
Riccardo Andrea Izzo, Gianluca Bardaro, Matteo Matteucci
This paper presents a novel approach to generating behavior trees for robots using lightweight large language models (LLMs) with a maximum of 7 billion parameters. The study demons…