One of the steps of teaching the Self-Driving Ads Robot (SEDRAD) how to navigate the environment is to teach it which surfaces are good for it to drive on. We began the tedious task of collecting images of the surrounding, and creating a segmentation of the images to later “teach” SEDRAD to recognize the surface to follow and stay on. This process comprises image acquisition, image annotation (segmenting in our case), and then segmentation validation. It is very time consuming. We also ran into a problem. Due to technical issues, the real SEDRAD was not available over the weekend, when we collected the data. Instead, we mounted the cameras at the same height and separation from each other on a wagon. Annotation here we go!