Perception

From small to complex, from robot vacuum cleaner to self-driving car: every robotic system needs some sort of perceptual capabilities in order to perceive information from its environment and to understand how it can manipulate it. Perception can come in many forms. Tim Patten gives a highly interesting introduction on how robots deal with object identification: what is it? (recognition), what type is it? (classification), where is it? (object detection), and how do I manipulate it? (grasping). The talk is suitable for beginners.

Michael Suppa from Roboception GmbH gives useful insights into robot perception applications in real-world environments. Roboception provides 3D vision hardware and software solutions that enable industrial robotic systems to perceive their environments in real-time. His talk introduces sensing principles, confidence and errror modelling, as well as pose estimation and SLAM (simultaneous localization and mapping). He also lists the requirements for real-world perception and manipluation systems in industrial environments.

Part 1: In the first part of his highly interesting lecture, Markus Vincze gives us useful insights into robotics visions and presents his vision of domestic robots. As an expert on 2D and 3D vision, he trains robots to understand the functions of objects and how they can help humans in everyday life situations. He shortly introduces two EU projects, HOBBIT and Squirrel, on domestic robots before diving deeper into tasks for robot vision in real-world environments (detection, grasping, placing). The lecture is suitable for beginners.

Part 2: In his follow-up lecture, Michael Beetz gives a short recap of his first talk before further exploring knowledge representation and reasoning for robotic agents. He focuses on one of the main problems of human-scale manipulation tasks for robotic systems, action description, when it comes to the performance of abstract tasks like "pour the water out". From "grasp the pot by the handles" to "tilt the pot around the axis between the handles" to "hold the lid while pouring", every action includes multiple intermediate tasks that have to be described in detail for the robot.

In their lecture, Jürgen Sturm and Christoph Schütte from Google Germany talk about the Google’s Cloud Robotics project before diving deeper into specific robot perception problems. Christoph Schütte introduces Cartographer, a system that provides real-time simultaneous localization and mapping, also called SLAM, in 2D and 3D across multiple platforms. Jürgen Sturm closes the lecture with semantic mapping and spatial intelligence in artificial intelligence.