A Multiagent Deep Reinforcement Learning Approach for Path Planning in Autonomous Surface Vehicles: The Ypacaraí Lake Patrolling Case

A Multiagent Deep Reinforcement Learning Approach for Path Planning in Autonomous Surface Vehicles: The Ypacaraí Lake Patrolling Case

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 agents is usually addressed with heuristics approaches, such as Reinforcement...

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Bibliographic Details
Main Authors: Samuel Yanes Luis, Daniel Gutierrez Reina, Sergio L. Toral Marin
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Deep reinforcement learning
multiagent learning
monitoring
path planning
autonomous surface vehicle
patrolling
Online Access:https://ieeexplore.ieee.org/document/9330612/

Internet

https://ieeexplore.ieee.org/document/9330612/

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