This paper shows a method for object pose detection that is successfully applied to industrial applications running a three-shift system. The industrial applications are fully automated feeding systems, commonly known as bin-picking. The proposed method is a generic approach to detect 6 degrees of freedom of any solid objects with arbitrary geometry. The proposed method is using 3D range data and is based on a hypothesize-and-test approach. In the first step, object poses are hypothesized by means of pose clustering. In the second step, the verification of estimated object poses is realised by an appearance-based template-matching approach. In addition, the method's interfaces are designed to ensure compatibility to 3D sensor systems and handling systems. During long-term operations in different use-cases, the method showed its usability regarding the crucial requirements, such as robustness, accuracy, portability and speed.
