67 citations · 85 across the 7 of their papers we have counts for
7 papers
Uncertainty Estimation for Deep Reconstruction in Actuatic Disaster Scenarios with Autonomous Vehicles
Samuel Yanes Luis, Alejandro Casado Pérez, Alejandro Mendoza Barrionuevo +3
Accurate reconstruction of environmental scalar fields from sparse onboard observations is essential for autonomous vehicles engaged in aquatic monitoring. Beyond point estimates,…
A Unified Experimental Architecture for Informative Path Planning: from Simulation to Deployment with GuadalPlanner
Alejandro Mendoza Barrionuevo, Dame Seck Diop, Alejandro Casado Pérez +3
The evaluation of informative path planning algorithms for autonomous vehicles is often hindered by fragmented execution pipelines and limited transferability between simulation an…
Beyond Task Performance: A Metric-Based Analysis of Sequential Cooperation in Heterogeneous Multi-Agent Destructive Foraging
Alejandro Mendoza Barrionuevo, Samuel Yanes Luis, Daniel Gutiérrez Reina +1
This work addresses the problem of analyzing cooperation in heterogeneous multi-agent systems which operate under partial observability and temporal role dependency, framed within…
Towards an Autonomous Surface Vehicle Prototype for Artificial Intelligence Applications of Water Quality Monitoring
Luis Miguel Díaz, Samuel Yanes Luis, Alejandro Mendoza Barrionuevo +5
The use of Autonomous Surface Vehicles, equipped with water quality sensors and artificial vision systems, allows for a smart and adaptive deployment in water resources environment…
Censored Deep Reinforcement Patrolling with Information Criterion for Monitoring Large Water Resources using Autonomous Surface Vehicles
Samuel Yanes Luis, Daniel Gutiérrez Reina, Sergio Toral Marín
Monitoring and patrolling large water resources is a major challenge for conservation. The problem of acquiring data of an underlying environment that usually changes within time i…
Data-Driven Methods for Present and Future Pandemics: Monitoring, Modelling and Managing
Teodoro Alamo, Daniel G. Reina, Pablo Millán Gata +2
This survey analyses the role of data-driven methodologies for pandemic modelling and control. We provide a roadmap from the access to epidemiological data sources to the control o…
Data-Driven Methods to Monitor, Model, Forecast and Control Covid-19 Pandemic: Leveraging Data Science, Epidemiology and Control Theory
Teodoro Alamo, D. G. Reina, Pablo Millán
This document analyzes the role of data-driven methodologies in Covid-19 pandemic. We provide a SWOT analysis and a roadmap that goes from the access to data sources to the final d…