To enable a smooth co-existence between robots and human workers in an industrial setting, we implemented two robot working memory configurations onto a mobile manipulator RB-KAIROS+ robot (Robotnik): A GRU-based one and a bioinspired alternative called WorkMATe which enabled the robot to adapt its navigation strategy depending on the presence of human workers. To evaluate the two working memory configurations against a non adaptive behavior, we tested a possible co-working scenario between two ostensible workers and the RB- KAIROS+ robot navigating in two mocked industrial set-ups. The application of behavioral adaptation through a working memory component was highly beneficial as it led to reduced energy consumption and, more importantly, to fewer acceleration anomalies in robot navigation than the non adaptive one. This suggests that a robot’s adaptive navigation through working memory can increase workers’ safety and improve the efficiency of the human-robot system as a whole in industrial applications.

The generalizability of empirical research depends on the reproduction of findings across settings and populations. Consequently, generalizations demand resources beyond that which is typically available to any one laboratory. With collective interest in the joint Simon effect (JSE) -- a phenomenon that suggests people work more effectively with humanlike (as opposed to mechanomorphic) robots -- we pursued a multi-institutional research cooperation between robotics researchers, social scientists, and software engineers. To evaluate the robustness of the JSE in dyadic human-robot interactions, we constructed an experimental infrastructure for exact, lab-independent reproduction of robot behavior. Deployment of our infrastructure across three institutions with distinct research orientations (well-resourced versus resource-constrained) provides initial demonstration of the success of our approach and the degree to which it can alleviate technical barriers to HRI reproducibility. Moreover, with the three deployments situated in culturally distinct contexts (Germany, the U.S. Midwest, and the Mexico-U.S. Border), observation of a JSE at each site provides evidence its generalizability across settings and populations.

In the present study, we compared Japanese and German participants' perceptions of social robots. To do so, participants from both cultural backgrounds evaluated two types of service robots designed for use in the smart home context. One of the prototypes featured a rather technical appearance, whereas the other prototype featured a newly designed social robot head. Against our predictions, Japanese and German participants evaluated both robot types similarly. Japanese participants generally showed a stronger tendency to anthropomorphize nonhuman agents and attributed more mind, particularly on the experience dimension, to both robot types than German participants. Nonetheless, Japanese and German participants attributed similar levels of agency to both robot types. Unexpectedly, Japanese participants perceived the robots even as less humanlike than German participants. As predicted, Japanese participants reported less attitudinal robot acceptance and tended to show less trust toward both robot types than Germans. Japanese and Germans indicated similar levels of robot anxiety, perceived uncanniness, and robot likeability. Japanese and German participants generally perceived the robots rather as machines and tools than as human companions. Especially German participants wanted to use the robots for rather safe, boring, and simple tasks that do not require any direct interaction with them. Japanese and German participants were not yet familiar with robots and showed less positive attitudes toward them than widely believed (e.g., [1]). Implications how to gain a more realistic view on users' perceptions of robots to enable a fruitful and comfortable HRI are discussed.

Previous research has shown that user features like affect, personality traits, user gender, technology commitment, perceived ease of technology use, and the feeling of being observed impact human-technology interaction (e.g., [1], [2]). To date, most studies have focused on the influence of user characteristics while interacting with single technical devices such as smart phones, audio players (e.g., [3]), or computers (e.g., [1]). To extend this work, we investigated the influence of individual user characteristics, the perceived ease of task completion, and the feeling of being observed on human-technology interaction and human-robot interaction (HRI) in particular. We explored how participants would solve seven tasks within a smart laboratory apartment. To do so, we collected video data and complemented this analysis with survey data to investigate naïve users' attitudes towards the smart home and the robot. User characteristics such as agreeableness, low negative affect, technology acceptance, low perceived competence regarding technology use, and the perceived ease of task were predictors of positive user experiences within the intelligent robotics apartment. Regression analyses revealed that a positive evaluation of the robot was predicted by positive affect and, to a lesser extent, by technology acceptance. Actual interactions with the robot were predicted by a positive evaluation of the robot and, to a lesser degree, by technology acceptance. Moreover, our findings show that user characteristics and, by tendency, the ease of task impact HRI within an intelligent apartment. Implications for future research on how to investigate the interplay of user and further task characteristics to improve HRI are discussed.