12 papers
Robots Ask the Way: Communication-Enabled Social Navigation
Valentino Sacco, Luca Scofano, Indro Spinelli +1
Assistive autonomous robots operating in multi-agent environments require efficient strategies to locate specific individuals among multiple residents. Current social navigation me…
T-Rex: Tactile-Reactive Dexterous Manipulation
Dantong Niu, Zhuoyang Liu, Zekai Wang +31
The ability to react dynamically to tactile signals has long been considered crucial to agile human-level dexterity. Yet contemporary learning-based Vision-Language-Action (VLA) mo…
Contrastive Action-Image Pre-training for Visuomotor Control
Yuvan Sharma, Dantong Niu, Anirudh Pai +16
Existing vision encoders for robotics face a fundamental bottleneck: robotic datasets lack the scale necessary for large-scale pre-training. Prior work circumvents this data scarci…
Bimanual Robot Manipulation via Multi-Agent In-Context Learning
Alessio Palma, Indro Spinelli, Vignesh Prasad +4
Language Models (LLMs) have emerged as powerful reasoning engines for embodied control. In particular, In-Context Learning (ICL) enables off-the-shelf, text-only LLMs to predict ro…
Describe-Then-Act: Proactive Agent Steering via Distilled Language-Action World Models
Massimiliano Pappa, Luca Romani, Valentino Sacco +5
Deploying safety-critical agents requires anticipating the consequences of actions before they are executed. While world models offer a paradigm for this proactive foresight, curre…
TI-PREGO: Chain of Thought and In-Context Learning for Online Mistake Detection in PRocedural EGOcentric Videos
Leonardo Plini, Luca Scofano, Edoardo De Matteis +6
Identifying procedural errors online from egocentric videos is a critical yet challenging task across various domains, including manufacturing, healthcare, and skill-based training…