面向边缘智能光学感知的航空紧固件旋转检测 |
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引用本文: | 符长虹,陈锟辉,鲁昆瀚,郑光泽,赵吉林.面向边缘智能光学感知的航空紧固件旋转检测[J].应用光学,2022,43(3):472-480. |
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作者姓名: | 符长虹 陈锟辉 鲁昆瀚 郑光泽 赵吉林 |
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作者单位: | 同济大学 机械与能源工程学院,上海 201804 |
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基金项目: | 上海市“科技创新行动计划”自然科学基金项目(20ZR1460100) |
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摘 要: | 针对航空紧固件分拣过程中现有方法存在效率低、成本高、精度差等问题,提出一种面向边缘智能光学感知的旋转目标检测方法。构建一种基于强化语义和优化空间的特征融合机制,有效提升目标检测模型的性能;设计一种空洞幻影模块,减少特征融合网络的参数量,有利于模型在工业场景下的边缘部署;采用高斯类环形平滑标签方法,在模型检测层预测分支上实现旋转目标检测,显著提升模型检测性能,并更有助于工业机器人自动抓取。在权威公开旋转数据集上,检测准确率达到77.16%。最后,在嵌入式智能设备上进行边缘部署并测试,整体准确率达到99.76%,推理速度超过20 FPS (frames per second),满足工业应用的要求。
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关 键 词: | 航空紧固件 旋转目标检测 特征融合 空洞幻影模块 边缘部署 |
收稿时间: | 2022-03-07 |
Aviation fastener rotation detection for intelligent optical perception with edge computing |
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Institution: | School of Mechanical Engineering, Tongji University, Shanghai 201804, China |
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Abstract: | Aiming at the problems of low efficiency, high cost and poor accuracy in existing methods in aviation fastener sorting process, a rotation target detection method for intelligent optical perception with edge computing was proposed. To further improve the performance of the target detection model, a feature fusion mechanism based on enhanced semantics and optimized space was constructed. A type of dilated ghost module to lower the parameter quantity of the feature fusion network was designed, and enable the edge computing deployment in industrial scenes. Using the Gaussian-like circular smooth label method, the rotation target detection was realized on the prediction branch of the model detection layer, which significantly enhanced model detection performance and was more favorable for automated grasping of industrial robots. The detection accuracy on the authoritative public rotation dataset reached 77.16%. Finally, the proposed detection method was implemented in an embedded intelligent device. The edge computing deployment shows that the total accuracy reaches 99.76%, and the inference speed is more than 20 frames per second (FPS), which is sufficient for industrial applications. |
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