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考虑海洋电流干扰的AUV路径规划基于云桌面技术

Siyuan Hu1, Shuai Xiao2, Jiachen Yang2

  • 1School of Futrue Technology, Tianjin University, Tianjin 300072, China.

Sensors (Basel, Switzerland)
|September 9, 2023
PubMed
概括

自主水下车辆 (AUV) 使用新的N-DDQNP模型来有效地规划路径,在动态海洋中导航. 这种人工智能方法改善了探索,并减少了复杂海洋环境中的导航时间.

关键词:
云桌面 云桌面 云桌面深度学习是一种深度学习.海流是目前的海洋流.海洋数据 海洋数据路径规划路径规划路径规划

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