Robotic systems that are able to adapt to individual humans through long-term or life-long experience and learning pave the way towards closer collaboration and interaction in a variety of application domains. In my talk I will outline recent scientific advances towards this aim, accomplished in a number of different robotics projects. I will discuss the potential benefits of long-term autonomy and adaptation as well as its challenges and how they can be addressed in terms of machine learning, software engineering, human-robot interaction, and artificial intelligence. Application domains to be presented in my talk will range from service applications of mobile robots in care and security, to individualised collaboration between manipulating robots and humans in manufacturing settings.
In particular, I'll show examples from our research covering the perception, interpretation, and adaptation of human motion and activity (using qualitative spatial relations), probabilistic models of task engagement and prediction, as well as continuous integration and testing in robotic software development.
Model-driven software engineering has gained momentum in academia as well as in industry for improving the development of evolving software by providing appropriate abstraction mechanisms in terms of software models and transformations thereof. With the rise of cyber-physical systems in general, and cyber-physical production systems in particular, the interplay between several engineering disciplines, such as software engineering, mechanical engineering and electrical engineering, becomes a must. Thus, a shift from pure software models to system models has to take place to develop the full potential of model-driven engineering for the whole production domain. System Models are also essential to raise the level of flexibility of production systems even further in order to better react to changing requirements, since systems are no longer designed to be, but they have to be designed to evolve. In this talk, we will present ongoing work of applying and further developing model-driven t
echniques, such as consistency management and co-evolution support, for the production domain.
Gerti Kappel is full professor at the Institute of Software Technology and Interactive Systems at TU Wien, chairing the Business Informatics Group. Until 2001, she was a full professor of computer science and head of the Department of Information Systems at the Johannes Kepler University of Linz. From 2004 to 2007, she acted as dean of studies for Business Informatics. She is head ("Sprecher") of the Doctoral College "Adaptive Distributed Systems", and a faculty member in the Doctoral College "Cyber-Physical Production Systems", both funded by TU Wien. Since 2014, she is also a board member of the Austrian Science Fund (FWF). Her current research interests include Model Engineering, Web Engineering, and Process Engineering.