Abstract:
The visual measurement of deep holes in composite material workpieces constitutes a critical step in the robotic assembly of aerospace components. The positioning accuracy of assembly holes significantly impacts the assembly quality of components. However, the complex texture of the composite material surface and mutual interference between the imaging of the inlet and outlet edges of deep holes significantly challenge hole detection. A visual measurement method for deep holes in composite materials based on the radial penalty Laplacian operator is proposed to address the issues by suppressing visual noise and enhancing the features of hole edges. Coupled with a novel inflection-point-removal algorithm, this approach enables the accurate detection of holes with a diameter of 10 mm and a depth of 50 mm in composite material components, achieving a measurement precision of 0.03 mm.
摘要:
复合材料工件深孔的视觉测量是航空航天部件机器人装配的关键步骤。装配孔的定位精度对零件的装配质量有很大影响。然而,复合材料表面的复杂纹理和深孔入口和出口边缘成像之间的相互干扰对孔检测提出了极大的挑战。提出了一种基于径向惩罚拉普拉斯算子的复合材料深孔视觉测量方法,通过抑制视觉噪声和增强孔边缘特征来解决该问题。再加上一种新颖的拐点去除算法,这种方法能够精确检测复合材料部件中直径为10毫米、深度为50毫米的孔,实现0.03毫米的测量精度。