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关于多个AUV协作检测和围绕攻击模拟的研究

Zhiwen Wen1, Zhong Wang1, Daming Zhou2

  • 1Xi'an Precision Machinery Research Institute, Xi'an 710077, China.

Sensors (Basel, Switzerland)
|January 23, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了用于海上任务的协调多AUV系统. 它使用先进的算法来实现高效的传输,检测和攻击,提高作战能力.

关键词:
在 AUV 形成过程中,AUV 形成.这是LSTM的LSTM.人工潜力领域的人工潜力领域协作检测 协作检测是一种协作式的检测.协作式的包围攻击.路径规划路径规划路径规划

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科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 人工智能的人工智能
  • 海洋工程 海洋工程

背景情况:

  • 单一自动水下车辆 (AUV) 的运营范围和效率有限.
  • 当代海洋环境需要超越单一AUV的增强能力.
  • 协调的多AUV系统对于复杂的任务越来越重要.

研究的目的:

  • 提出一个综合解决方案,协调多AUV形成的发展.
  • 为了实现远程渡轮,协调检测和周围攻击任务.
  • 提高水下机器人系统的运营效率和范围.

主要方法:

  • 使用快速探索随机树 (RRT) 算法进行无碰撞路径规划.
  • 人工潜力场方法,用于保持阵列完整性和在检测过程中避免障碍物.
  • 长短期记忆 (LSTM) 网络和深度决定性政策梯度 (DDPG) 用于在攻击期间的预测准和形成控制.

主要成果:

  • 在最初的渡轮阶段证明了无碰撞的运动.
  • 成功地保持了AUV形成完整性,并在协调检测期间适应环境变化.
  • 增强预测能力和有效的阵营控制,用于协调攻击机动.

结论:

  • 拟议的多AUV协调解决方案有效地解决了复杂的海洋任务要求.
  • 结合路径规划,潜力场,LSTM和DDPG的综合方法提高了AUV的作战能力.
  • 模拟结果验证了系统在协调运输,检测和攻击任务中的有效性.