获取工件目标位置和姿态的信息是实现工业机器人准确地抓取工件的关键。提出了一种用单目相机对随机堆放工件的目标进行识别和定位的方法。采用基于物体三维CAD模型的几何信息进行模板训练，对轮廓分明的工件可以实现高效的识别。结合高效的金字塔模型分层搜索策略,以及具有归一化相似性度量的匹配方式，保证了全局域范围内能训练出最合适的模板。测试目标对象是轮廓明显、具有反光特性的金属保持架工件，在随机堆放工件中进行了识别定位的实验。实验结果表明，用该方法可以准确识别随机堆放工件中的目标，目标工件在X，Y，Z轴方向上的平均定位误差为0.948 mm、1.078 mm、2.175 mm。

Accurate recognition and location of randomly placed industrial parts is the key technology to realized intelligent bin-picking of industrial robot. An approach to recognition and location of target object in randomly placed industrial parts using monocular camera. Efficient recognition of industrial parts with distinct profile could be realized when the geometric information based on 3D CAD model is used to train the temple. The most appropriate temple was obtained after the combination of a pyramid approach with hierarchical model views and the matching mode characterize by normalized similarity measure. The tested objective is a metal couple cage with distinct profile and reflective feature. Some experiments were carried out for randomly placed parts. Experimental results show that the target can be recognized accurately in randomly placed parts. The average location errors of target parts in X, Y and Z direction are 0.948 mm, 1.078 mm and 2.175 mm.