6 papers
IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation
Jelin Raphael Akkara, Filippo Ziliotto, Luciano Serafini +2
Embodied AI increasingly relies on queryable semantic maps built from pre-trained vision-language models to enable zero-shot Object Goal Navigation (ObjectNav). However, existing a…
What VGGT Knows About Overlap: Probing Geometric Foundation Models for Co-Visibility
Filippo Ziliotto, Luciano Serafini, Lamberto Ballan +1
A fundamental challenge in 3D reconstruction and robotic localization is co-visibility: determining which image pairs share overlapping visible surfaces, particularly in scenarios…
PersONAL: Towards a Comprehensive Benchmark for Personalized Embodied Agents
Filippo Ziliotto, Jelin Raphael Akkara, Alessandro Daniele +3
Recent advances in Embodied AI have enabled agents to perform increasingly complex tasks and adapt to diverse environments. However, deploying such agents in realistic human-center…
MLFM: Multi-Layered Feature Maps for Richer Language Understanding in Zero-Shot Semantic Navigation
Sonia Raychaudhuri, Enrico Cancelli, Tommaso Campari +3
Recent progress in large vision-language models has driven improvements in language-based semantic navigation, where an embodied agent must reach a target object described in natur…
TANGO: Training-free Embodied AI Agents for Open-world Tasks
Filippo Ziliotto, Tommaso Campari, Luciano Serafini +1
Large Language Models (LLMs) have demonstrated excellent capabilities in composing various modules together to create programs that can perform complex reasoning tasks on images. I…
Following the Human Thread in Social Navigation
Luca Scofano, Alessio Sampieri, Tommaso Campari +4
The success of collaboration between humans and robots in shared environments relies on the robot's real-time adaptation to human motion. Specifically, in Social Navigation, the ag…