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Updated: Jul 27, 2025

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基于目标检测的存档管理机器人控制方法

Cheng Yan1, Jieqi Ren2, Rui Wang1

  • 1College of Automation, Nanjing University of Science & Technology, Xiaolingwei Street, Nanjing 210094, China.

Sensors (Basel, Switzerland)
|June 10, 2023
PubMed
概括
此摘要是机器生成的。

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本研究介绍了无人纸质档案的自适应机器人系统,提高了访问档案箱的可靠性和效率. 该系统利用YOLOV5和伺服控制进行准确的检索,性能优于当前的商业解决方案.

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
  • 档案科学 档案科学

背景情况:

  • 在大型无人设施中对高效档案管理的需求日益增加,需要可靠的机器人解决方案.
  • 由于高可靠性要求,现有系统在处理复杂的档案箱访问场景时面临挑战.

研究的目的:

  • 为无人环境提出和评估一种具有适应性识别的新型纸质档案访问系统.
  • 提高机器人系统在纸质档案管理中的准确性和可靠性.

主要方法:

  • 开发一个与视觉组件集成的伺服控制机器人手臂系统.
  • 利用YOLOV5算法用于特征区域识别和目标中心位置估计.
  • 实现基于特征区域的分类和匹配算法与闭环伺服控制.

主要成果:

  • 拟议的系统表现出更高的准确性,在受限制的观看场景中,震动概率降低了1.27%.
  • 实验结果显示,与现有的商业档案管理机器人系统相比,存储成功率更高.
  • 与升降装置的集成使不同高度的档案箱能够有效存储和检索.

结论:

  • 适应盒访问系统是用于无人设置中复杂的纸质档案管理的可靠和经济有效的解决方案.
关键词:
这就是YOLOV5的意义.位置估计位置估计.机器人手臂是一个机器人.无人机档案存储库是一个无人机存储库.

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  • 该系统显示了提高无人档案存储效率的巨大潜力.
  • 需要进一步的研究来评估系统的可扩展性和通用性.