Seminar Talk

Abstract: In the future, robots are expected to work as a companion with humans in various areas ranging from service robots to humanoid robots. Dynamic and unpredictable human/domestic environments force developers to improve safety for human-robot cooperation. One natural approach for humans is to warn about threats using natural spoken language. Then, robots should be able to modulate safer actions by a syntactic/semantic understanding of those warnings. In pour research deep neural networks will be used as the main learning approach of the natural language processing part. However, besides warning messages, other modalities seem necessary to gain a better understanding of threats such as prosody and vision. Generating safer actions depending on context can be performed by reinforcement learning or simply by choosing from an available action set. Moreover, possible tasks and scenarios as well as datasets and platforms will be discussed in this talk