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水下机器人的基于摄像头的网络回避控制.

Jonghoek Kim1

  • 1System Engineering Department, Sejong University, Seoul 5006, Republic of Korea.

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|January 26, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种方法,让水下机器人使用基于摄像头的深度神经网络来避开捕鱼网. 机器人突然远离被检测到的网,以确保安全导航和目标实现.

关键词:
基于摄像头的网络检测.净规避控制 净规避控制反应性控制法则 反应性控制法则水下机器人 水下机器人

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科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 计算机视觉 计算机视觉
  • 人工智能的人工智能

背景情况:

  • 由于渔网等障碍,水下机器人面临重大导航挑战.
  • 检测和避免渔网对于任务的成功和在未知的水生环境中机器人的安全至关重要.
  • 被动摄像头传感器提供有限的信息,例如轴承角度,但缺乏直接测量网距离.

研究的目的:

  • 为水下机器人制定反应性控制策略,以避免渔网.
  • 为了使机器人能够在未知的环境中实现目标,尽管存在渔网.
  • 通过摄像头传感器利用深度神经网络进行水下网络检测.

主要方法:

  • 使用深度神经网络来检测渔网,使用水下机器人摄像头数据.
  • 实施反应性避开机动:在检测到网时突然向后移动.
  • 在摄像头图像中使用检测到的网的界限框来指导避开.
  • 在向后移动后执行一个大圆形转,以重新定向目标,同时保持与网的安全距离.

主要成果:

  • 拟议的方法允许机器人有效地避免检测到的渔网.
  • 模拟演示了反应性控制规律的成功应用,以实现净规避.
  • 该策略使机器人能够朝着目标前进,同时减轻纠风险.

结论:

  • 开发的反应控制规则为在渔网周围的水下机器人导航提供了独特的解决方案.
  • 基于摄像头的网络检测与突然避开机动相结合,提高了机器人的安全性和任务能力.
  • 这种方法在模拟中是有效的,并为现实世界水下机器人操作提供了一个有希望的方向.