Open World Robotics

AI offers an enormous potential in terms of improving the effectiveness and efficiency of robots. In recent years, data-driven AI has achieved remarkable success in specialised tasks such as speech recognition, machine translation and object detection. Despite these successes, there are also some clear signs of the limitations.

On finding a solution to these limitations, we study the following three challenges:

1) How may robots operate under real-world conditions, which are dynamic and packed with unknown objects and situations?
2) How may robots be able to execute multiple tasks, instead of just one?
3) How can robots cooperate with other robots and with human team-mates?

In this talk the first two challenges will be addressed. Also, we will show how the knowledge-base of TypeDB enables us to tackle such challenges.

Speaker: Joris Sijs, Scientist @ TNO
Joris is a team-lead at TNO, where he develops and integrates software modules for the perception, awareness and planning of autonomous systems and autonomous robots. He recently started to extend this work with the development of knowledge-graphs (or cognitive databases), and how to combine this type of AI with the machine- and deep-learning solutions in AI.