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Artículo
A Deep Reinforcement Learning Approach for the Patrolling Problem of Water Resources Through Autonomous Surface Vehicles: The Ypacarai Lake Case
(Institute of Electrical and Electronics Engineers, 2020)
Autonomous Surfaces Vehicles (ASV) are incredibly useful for the continuous monitoring and exploring task of water resources due to their autonomy, mobility, and relative low cost. In the path planning context, the ...
Artículo
An evolutionary multi-objective path planning of a fleet of ASVs for patrolling water resources
(Elsevier, 2022-03)
The rapid increase of human activities with direct influence on the environment has motivated the global awareness of the need to efficiently monitor the natural resources. Among the wide range of problems addressed, such ...
Artículo
A Multiagent Deep Reinforcement Learning Approach for Path Planning in Autonomous Surface Vehicles: The Ypacaraí Lake Patrolling Case
(Institute of Electrical and Electronics Engineers Inc., 2021)
Autonomous surfaces vehicles (ASVs) excel at monitoring and measuring aquatic nutrients due to their autonomy, mobility, and relatively low cost. When planning paths for such vehicles, the task of patrolling with multiple ...
Artículo
A Dimensional Comparison between Evolutionary Algorithm and Deep Reinforcement Learning Methodologies for Autonomous Surface Vehicles with Water Quality Sensors
(MDPI, 2021)
The monitoring of water resources using Autonomous Surface Vehicles with water-quality sensors has been a recent approach due to the advances in unmanned transportation technology. The Ypacaraí Lake, the biggest water ...
Artículo
Censored deep reinforcement patrolling with information criterion for monitoring large water resources using Autonomous Surface Vehicles
(Elsevier, 2023-01)
Monitoring and patrolling large water resources is a major challenge for nature conservation. The problem of acquiring data of an underlying environment that usually changes within time involves a proper formulation of the ...