School students

Part 5: This presentation is about how a robot decides on its actions in everyday life. For this purpose, there are some important exciting cognetive models that David Vernon explains and compares them with each other.

Part 4: In this presentation John Leird talks about the integration of perception and action in the soar cognitive architecture. In addition, exciting theses concerning cognition in psychology are included.

Part 3: In this presentation Axel Ngonga explains with the help of a cooking robot the interesting approach of the class expression learning with multiple representations. 

Part 2: In this lecture Antonio Lieto tells interesting facts about commonsense reasoning frameworks for dynamic knowledge invention via conceptual combination and blending. For this purpose, real problems and approaches to solutions are used and addressed.

Part 1: The first talk will start with a short review of some basics of AI and computer science. Michael Beetz will also present some interesting examples in the world of cognition-enabled manipulation. 

Integrating advanced skills into robotic systems for reliable autonomous operation is a pressing challenge. Current robot software architectures, many based on the 3-layers paradigm, are not flexible to dynamically adapt to changes in the environment, the mission or the robot itself (e.g. internal faults).

THE SYNTAX OF ACTION

Path planning is a core problem in robotics. Lydia Kavraki developed a method called the Probabilistic Roadmap Method (PRM), which caused a paradigm shift in the robotics community. The approach introduced randomization schemes that exploited local geometric properties and produced efficient solutions without fully exploring the underlying search space.

There’s a common misconception that decisions made by computers are automatically unbiased – as opposed to those made by humans. However, Chad Jenkins pointed out many ways in which AI can fail to deliver fair and reasonable results. He pointed out what needs to be done in AI to get the intellectual domain right and how the technology and understanding researchers generate can have a positive impact on the world.

Jan Andersen is Head of Research Office at the University of Southern Denmark. He has a background in Computer Science and Danish Language. He has been working with research strategy and research planning. He was involved in building up four very successful research support units. He was an advisor for Rectors of the Danish Technical University, University of Copenhagen, and the former Royal Veterinary and Agricultural University. He was responsible for the cross-faculty follow-up of the Danish university merger in 2007.