DSSE:强化学习无人机群海上搜救模拟环境

Renato Laffranchi Falcão, Jorás Custódio Campos de Oliveira, Pedro Henrique Britto Aragão Andrade, Ricardo Ribeiro Rodrigues, Fabrício Jailson Barth, J. F. B. Brancalion
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引用次数: 0

摘要

该项目的目标是利用强化学习技术推进海上搜救任务的研究。该软件为研究人员提供了两种截然不同的环境:一种环境模拟了随海流漂流的遇难船员,为训练和评估自主代理创造了随机环境;另一种环境则采用了逼真的粒子模拟,用于绘制和优化自主代理的搜索区域覆盖范围。这两个环境都遵循开源标准,并提供广泛的定制选项,使用户能够根据具体研究需求进行定制。这些工具使强化学习代理能够学习高效的策略,以确定遇难人员的位置或最大限度地扩大搜索区域的覆盖范围,从而提高海上救援行动的效率。
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DSSE: An environment for simulation of reinforcement learning-empowered drone swarm maritime search and rescue missions
The goal of this project is to advance research in maritime search and rescue missions using Reinforcement Learning techniques. The software provides researchers with two distinct environments: one simulates shipwrecked people drifting with maritime currents, creating a stochastic setting for training and evaluating autonomous agents; the other features a realistic particle simulation for mapping and optimizing search area coverage by autonomous agents. Both environments adhere to open-source standards and offer extensive customization options, allowing users to tailor them to specific research needs. These tools enable Reinforcement Learning agents to learn efficient policies for locating shipwrecked individuals or maximizing search area coverage, thereby enhancing the effectiveness of maritime rescue operations
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