3D object recognition for coordination-less bin-picking automation

Abstract

At present, industrial robots are required to support high-mix low-volume production, which calls for automation and flexibility in production lines. To realize these requirements, it is necessary that automate of bin picking. In this work, we propose a three-dimensional object recognition using deep learning to automate coordination-less bin picking. The deep learning-based method requires the use of training data, but it has the higher cost of annotating the training data. Therefore, we construct a coordination-less recognition model by using the automatic acquisition method for training data in a simulation environment. For the evaluation, we conducted experiments in a simulation and real environment to verify the accuracy of the proposed method.