This paper introduces a new companion robot as an open research platform for studying human-robot interaction: The ZENIT Enabling Natural Interaction Technology. Open-source solutions for companion robots are often complicated to build or not thought of holistically. ZENIT is based on a few low-cost components, namely a smartphone and a stationary robot arm in conjunction with an average computer and a separate camera. This concept makes it possible not to be tied to specific hardware. Our platform aims to enable easy use of the multimodality of human communication channels such as body language, spatial behavior, facial expressions and speech so that ZENIT can understand its interlocutor and express itself appropriately. The fusion of various open-source software components in an adaptable, lightweight and resource-efficient distributed system simplifies its replication. The system demonstrated an adequate response time (speech: 2.69s, facial expressions: 0.55s, bodily movements: 0.32s) for perception and expression combined, as well as reliability in public testing. Evaluation of the robot’s expressive capabilities in an online survey (N=23) revealed users were able to understand six of eight emotions conveyed by ZENIT using facial expressions and/or body language (except for contempt and fear) and perceived its non-verbal feedback as significantly more expressive when facial expressions were accompanied with bodily movements.

The visual representation of human-like entities in virtual worlds is becoming a very important aspect as virtual reality becomes more and more "social". The visual representation of a character's resemblance to a real person and the emotional response to it, as well as the expectations raised, have been a topic of discussion for several decades and have been debated by scientists from different disciplines. But as with any new technology, the findings may need to be reevaluated and adapted to new modalities. In this context, we make two contributions which may have implications for how avatars should be represented in social virtual reality applications. First, we determine how default and customized characters of current social virtual reality platforms appear in terms of human likeness, eeriness, and likability, and whether there is a clear resemblance to a given person. It can be concluded that the investigated platforms vary strongly in their representation of avatars. Common to all is that a clear resemblance does not exist. Second, we show that the uncanny valley effect is also present in head-mounted displays, but-compared to 2D monitors-even more pronounced.

Virtual reality becomes a medium to be explored for itself, to study human factors and human behavior within these worlds, and to infer possible behavior in the real world. Among many advantages, building test routines in virtual environments remains a challenge due to the lack of established procedures and toolkits. To encourage research in this direction and lower the barrier to entry, it is necessary to simplify the process of setting up a research environment in virtual reality by providing appropriate toolkits. This paper discusses what challenges need to be overcome, what features might be relevant, and compares available toolkits.

Technologies for Virtual, Mixed, and Augmented Reality (VR, MR, and AR) allow to artificially augment social interactions and thus to go beyond what is possible in real life. Motivations for the use of social augmentations are manifold, for example, to synthesize behavior when sensory input is missing, to provide additional affordances in shared environments, or to support inclusion and training of individuals with social communication disorders. We review and categorize augmentation approaches and propose a software architecture based on four data layers. Three components further handle the status analysis, the modification, and the blending of behaviors. We present a prototype (injectX) that supports behavior tracking (body motion, eye gaze, and facial expressions from the lower face), status analysis, decision-making, augmentation, and behavior blending in immersive interactions. Along with a critical reflection, we consider further technical and ethical aspects.