Students

CRAM (Cognitive Robot Abstract Machine) is a software toolbox for the design, the implementation, and the deployment of cognition-enabled autonomous robots performing everyday manipulation activities. CRAM equips autonomous robots with lightweight reasoning mechanisms that can infer control decisions rather than requiring the decisions to be preprogrammed. This way CRAM-programmed autonomous robots are much more flexible, reliable, and general than control programs that lack such cognitive capabilities.

RoboSherlock is a common framework for cognitive perception, based on the principle of unstructured information management (UIM). UIM has proven itself to be a powerful paradigm for scaling intelligent information and question answering systems towards real-world complexity.

The Robohow framework represents control programs as concurrent, percept-guided manipulation plans. It will use websites, visual instructions and haptic demonstration as primary information sources. These heterogeneous pieces of information will be integrated and combined with each other through an interface layer that provides an abstract machine for programming high-level robot manipulation plans. The interpreter for this abstract machine includes novel mechanisms for optimization and constraint-based movement specification, and percept-guided manipulation.

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.

Moritz Tenorth, CTO at the start-up Magazino GmbH, talks about mobile pick-and-place robots in industrial working environments. Magazino develops and builds customized industrial robots and robot platforms mainly used in logistics that serve as robot assistants to humans, for example to factory workers to keep their work environment safe and efficient. Moritz Tenorth gives us an idea of how challenging these tasks are and how they can be solved. He also shares his advice for a successful transition from academia to industry and the work in a real startup environment.

Part 3: In his third and final lecture, David Vernon discusses recent developments in cognition research. He addresses the common model of cognition that emcompasses approaches in Artificial Intelligence, Cognitive Science, Neuroscience, and Robotics. It is mainly based on the book "Unified theories of cognition" by Allen Newell, a leading investigator in computer science and cognitive psychology. Newell states that cognition takes place over multiple timescales (from millisecond-level to year-level and everything in between).

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.

Part 2: In his follow-up lecture, David Vernon dives deeper into the role of memory, especially in a system. Memory, as he states, is a process rather than a state. He presents different types of memory, explores the role of memory, explains the concept of self-projection, prospection, and internal simulation, and clarifies technical terminology from cognitive science and psychology as well as from robotic literature. He concludes with internal simulation combined with action, and with the concept of forgetting which is important but still not fully understood in neuroscience.

Part 1: In his first of three talks, David Vernon gives a concise and coherent overview of cognitive architecture. He begins by explaining the concept of cognition as an umbrella term that encompasses perception, learning, anticipation, action, and adaptation. Cognition allows robots to work independently in challenging environments, to adapt to changes, and to anticipate events in preparing their actions. If cognition was the top of a mountain and the goal to be achieved, architecture would be the base camp that needs to be set up first.