PhD 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).

In this course, David Vernon presents the 10th module of the "Design & Implementation of Cognition-enabled Robot Agents" series. The learning goals of this module enables you to:

This course consists of ten Modules that together provide an overview of the methods required to build a cognition-enabled robot agent. The picture on the right shows an overview of the modules. Each Module consists of several video lectures and an exercise. Some modules contain additional learning materials.

The video is a tutorial showing the basics of the CRAM framework, which is a toolbox for designing, implementing, and deploying software on autonomous robots. The aim of the tutorial is to (1) give an intuition of what knowledge the robot needs to execute even a simple fetch and place, (2) show how many different things can go wrong and teach writing simple failure handling strategies, and (3) make the user familiar with the API of the actions already implemented in the CRAM framework.

Bio:

THE SYNTAX OF ACTION