一个双阶段的螺丝检测框架,用于使用反射特征回归模型自动拆卸
Quan Liu1, Wupeng Deng1,2, Duc Truong Pham2
1School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China.
Micromachines
|May 27, 2023
概括
这项研究引入了用于再制造的自动化两级螺丝检测系统. 它可以准确地识别损坏的螺丝,即使在光线不均的情况下,提高自动拆卸效率.
科学领域:
- 工程 工程师 工程师 工程师
- 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
背景情况:
- 重制需要高效的自动拆卸过程.
- 自动拆除螺丝是退役产品拆卸的关键步骤.
- 现有的方法与受损的螺丝和可变的照明条件作斗争.
研究的目的:
- 开发一个强大的自动视觉检测框架,用于结构受损的螺丝.
- 为了在不均的照明下实现精确的螺丝检测,用于重制.
- 通过改进自动化,提高再制造的经济可行性.
主要方法:
- 一个两阶段的检测框架,利用反射和纹理特征.
- 一个线性回归模型的反射特征来处理不均的照明.
- 一个自我优化策略和加权的融合,以实现强大的检测.
主要成果:
- 该框架在复杂的场景中成功检测出结构损坏的螺丝.
- 该方法在不均的照明条件下显示出有效性.
- 在一个用于拆卸电动汽车电池的机器人平台上成功实施.
结论:
- 开发的框架允许在复杂的拆卸任务中自动拆除螺丝.
- 使用反射功能和数据学习为自动拆卸提供了新的方法.
- 这项研究有助于更具经济吸引力的重制工艺.
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