Before revision:  In this work, we propose training a neural network through large-scale domain randomization to identify the articulation type of object parts from a single image observation. Training data is generated via photorealistic rendering in simulation .
After revision:  In this work, we propose training a neural network through large-scale domain randomization to identify the articulation type of object parts from a single frame of an RGB-D image and segmentation masks. The network is trained on 100k synthetic images of 149 articulated objects from 6 categories. Synthetic images are rendered via a photorealistic simulator with domain randomization .