collaborators

5 papers

cs.RO2026

Generalization of World Models under Environmental Variability for Vision-based Quadrotor Navigation

Luca Zanatta, Grzegorz Malczyk, Kostas Alexis

World models, learned generative models that predict how an environment evolves, have become a promising tool for sample-efficient robot learning. Yet how robust they are to enviro…

cs.CV2026

Event-based Civil Infrastructure Visual Defect Detection: ev-CIVIL Dataset and Benchmark

Udayanga G. W. K. N. Gamage, Xuanni Huo, Luca Zanatta +4

Small unmanned aerial vehicle (UAV)-based visual inspections are a more efficient alternative to manual methods for examining civil structural defects, offering safe access to haza…

cs.RO2026

Cross-Modal Reinforcement Learning for Navigation with Degraded Depth Measurements

Omkar Sawant, Luca Zanatta, Grzegorz Malczyk +1

This paper presents a cross-modal learning framework that exploits complementary information from depth and grayscale images for robust navigation. We introduce a Cross-Modal Wasse…

cs.LG2025

Foundation Models for Structural Health Monitoring

Luca Benfenati, Daniele Jahier Pagliari, Luca Zanatta +6

Structural Health Monitoring (SHM) is a critical task for ensuring the safety and reliability of civil infrastructures, typically realized on bridges and viaducts by means of vibra…

cs.AR2025

SpikeStream: Accelerating Spiking Neural Network Inference on RISC-V Clusters with Sparse Computation Extensions

Simone Manoni, Paul Scheffler, Luca Zanatta +3

Spiking Neural Network (SNN) inference has a clear potential for high energy efficiency as computation is triggered by events. However, the inherent sparsity of events poses challe…