Interaction Architecture as basis for research

In order to provide a research environment that is capable to integrate different research perspectives and approaches one important objective is the development of a platform that allows different research groups to carry out their experiments and to develop their own applications within an ambient intelligent robotic apartment environment. Importantly, this includes the integration of the robot in the ambient environment infrastructure, i.e. to allow for smooth data exchange on the one hand as well as the possibility for joint control, supporting parallel interactions. Furthermore, the architecture should provide the capability for 24/7 operability. This objective is addressed by WP1.

Attention management in smart environments

Attention is a valuable resource for human users. The CSRA provides a uniq research platform to investigate attentional behavior in more natural situations in order to develop a consistent approach how an assistive system should address a user's attention. One important strand of research deals with the question how to keep the user's attention and how to behave attentively in foreground interactions. On the other hand we will investigate less resource demanding approaches in future research. This objective is addressed by WP2 Interaction Capabilities.

Situated speech synthesis

Current speech synthesis approaches target to optimize synthesis performance in lab environments. However, when being faced with tasks that are tedious, time-critical or very important to us and we are also subject to distractions, we are likely to change our expectations of the communicative style of an assistive system. Within the CSRA our objective is to provide speech synthesis approaches that are more robust in real life situations. This objective is addressed by WP2 Interaction Capabilities.

Memory

Current smart home solutions do not have the capability to memorize user idiosyncrasies or let alone interaction events, leading to repeating tedious interactions with the user. We therefore target to provide a functionality for developing a memory that provides an intelligent interface for applications that need history information for learning, interaction or other purposes. This objective is addressed in WP3 Memory and Learning.

Data reduction

Given the large number of sensors and actors, a smart robotic environment can produce huge amounts of data. It is therefore important to reduce the amount of information for storage and learning by intelligent methods of feature reduction. This objective is addressed in WP3 Memory and Learning.

Assessment of user preferences

User-driven development and research is driven by user studies. Our goal is to identify user preferences for interaction with a robotic apartment and preferences of the design of the hardware interfaces. This objective is addressed in WP4.