Exploration and Rescue of Shipwreck Survivors using Reinforcement Learning-Empowered Drone Swarms

The goal of this project is to create a reinforcement learning algorithm that locates shipwrecked individuals using a swarm of drones. A simulated environment was developed to train and visualize the outcome of the trained algorithm, considering the ocean's dynamic circumstances. This project does not discuss image recognition of shipwrecked people, since the true focus of this project is to optimize the search routine of a drone to find the target in the most efficient way possible. The implemented Reinforce algorithm takes into account a dynamic map of probabilities, representing the chances of a person being found, as well as the position of other agents. Outcomes include an open-source python package for the environment and the implementation of the reinforcement learning algorithm. The algorithm demonstrates superiority over the predefined approach, proving the advantages of reinforcement learning in efficiency and effectiveness.

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Publication Details

Journal
Aplicações Operacionais em Áreas de Defesa
Published
2025-09-23
DOI
https://doi.org/10.55972/spectrum.v26i1.421
Primary Topic
Marine Ecology and Invasive Species
Type
article
Field-Weighted Citation Impact
0.00
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article

Exploration and Rescue of Shipwreck Survivors using Reinforcement Learning-Empowered Drone Swarms

José Fernando Basso Brancalion, Fabrício J. Barth
Aplicações Operacionais em Áreas de Defesa
Marine Ecology and Invasive Species
article

Exploration and Rescue of Shipwreck Survivors using Reinforcement Learning-Empowered Drone Swarms

José Fernando Basso Brancalion, Fabrício J. Barth
article en

Abstract

The goal of this project is to create a reinforcement learning algorithm that locates shipwrecked individuals using a swarm of drones. A simulated environment was developed to train and visualize the outcome of the trained algorithm, considering the ocean's dynamic circumstances. This project does not discuss image recognition of shipwrecked people, since the true focus of this project is to optimize the search routine of a drone to find the target in the most efficient way possible. The implemented Reinforce algorithm takes into account a dynamic map of probabilities, representing the chances of a person being found, as well as the position of other agents. Outcomes include an open-source python package for the environment and the implementation of the reinforcement learning algorithm. The algorithm demonstrates superiority over the predefined approach, proving the advantages of reinforcement learning in efficiency and effectiveness.

Aplicações Operacionais em Áreas de DefesaVol. 26(1)
Embraer (Brazil) (BR), Insper (BR)
Openalex Percentile: Top 75%
Marine Ecology and Invasive Species
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