The latest progresses in AI and robotics allow to automate many repetitive and tiring tasks. As a result, the focus of many activities can be transferred to more proactive and stimulating aims. The work is focused on automating piece picking, that is one of the most common tasks in the majority of industrial/logistic environments. As a matter of fact, depending on the available robot gripper (vacuum), an algorithm should be able to correctly identify suitable contact points from an RGB+D image. AI applied to image segmentation is a convenient way to achieve such a goal. At first, a solid model in charge of highlighting each class of objects in a cluttered scene is adopted, using a predefined dataset suiting this specific task.