Human-robot interaction (HRI) can be defined as the field of study about understanding, designing, and evaluating the robotic systems used by or collaborating with the human operator (Sharkawy, 2021); and/or understanding this interaction from both the human and robot perspectives; and/or extending the parties in interaction from the human operator to all individuals who are affected by the robot due to its’ vicinity. The difficulty in finding an appropriate definition for human-robot interaction reflects, at least, the novelty of it.
The application area of human-robot interaction is vast, including, for example, planning or coordination between the tasks for human and robot in collaboration or interaction, and programming. In this scope, human-robot task allocation and scheduling, metrics for HRI, social aspects, programming also including user interface related issues such as visual guidance and imitation, voice commands and haptic interaction as well as physical HRI and safety related issues are included (Tsarouchi, Makris, Chryssolouris, 2016). Studies have also been made in a smaller scope, such as the features of robot gaze behaviour and appearance that improve interaction (Admoni, Scassellati, 2017).
The difficulty in defining features in human-robot interaction is that the term ‘robot’ is not accurate. There are several types of robots, enabling different types of human-robot interaction. At least robot’s task and task-related functionalities and how they are realised, and in what way human is supposed to interact with the robot, are crucial factors to take into account. General-level rules are hard to provide.
Human-robot interaction experience is shaped by human and robot but not in a symmetrical way. From the human perspective, it depends on how a person perceives and experience the interaction. From the robot-centric view, the design of the robot (visual, behaviour, etc.) affects interaction experience. In both cases it is the human, of course, who perceives (Young, Sung, Voida, Sharlin, Igarashi, Christensen, Grinter, 2011). Young et al. (Young et al., 2011) have identified three main factors contributing to this interaction – visceral factors, social mechanics, and social structures.

Visceral factors of interaction focus on a person’s biological, visceral, and instinctual involvement in interaction. This includes such things as frustration, fear, joy, happiness, and so on, as an “instinctual” reaction to robot, in the level where they are difficult to control.
Social mechanics refer to the higher-level communication and social techniques in interaction. This includes both the social behaviour of a person when interacting with the robot and how the person interprets robot’s behaviour from the social perspective. Social mechanics function in many levels, starting from facial expressions and gestures to spoken language and cultural social behaviour related norms (such as the size of personal space and eye-contact rules).
Social structures cover the development and changes in the interaction between human and robot over a longer period of time.
These factors (visceral factors as well as social mechanics and structures) are probably the more relevant the more the robot resembles a human being by appearance and behaviour, especially depending on how autonomous the robot is or appears to be from the human’s perspective. Regarding robots to be used at the building site, these factors do not probably play as relevant role as with robots, which are used, for example, in health care in nursing related activities.
Robots can be used in environments that are unreachable by or are unsafe for human beings. Then, effective human-robot partnership needs to be established. Trust is a prerequisite for this, affecting the successfulness of human-robot interaction. It was found in a review (Hancock, Billings, Schaefer, Chen, De Visser, Parasuraman, 2011) that when the effects of human, robot, and environmental characteristics were studied, the robot performance-based factors, such as robot behaviour and the reliability of the robot were the strongest contributors to the development of trust in HRI. Environment, defined as team collaboration characteristics and tasking-related factors in this study, played only a moderate role in this. Only a little evidence was found on human-related factors that were related to human abilities and characteristics in this study. This may not be the case in reality but the small number of studies found in this area can be the reason for this result.
From the studying perspective, human-robot interaction is such a vast concept that in practice, almost anything can be labelled as belonging to it, provided that the core parties – human and robot – are both included in it. In practice, from BIMprove perspective, the meaning of human-robot interaction depends on the qualities of the specific robot in question. If the robot is, for example, moving around the site, safety related issues need to be identified in human-robot interaction. If the robot is stationary, a usability or user-experience based evaluation may be all that is needed.

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  • Admoni, H., & Scassellati, B. (2017). Social eye gaze in human-robot interaction: a review. Journal of Human-Robot Interaction, 6(1), 25-63.
  • Aust, M., Otto, M., Helin, K. (2020). BIMprove User Interfaces: Multi-User-XR for construction (Poster). In: Helin, K., de Antonio, A., Reyes-Lecuona, A. (Editors): EuroVR 2020 Application, Exhibition & Demo Track: Proceedings of the Virtual EuroVR Conference, ISBN 978-951-38-8741-4, 71-75.
  • Hancock, P. A., Billings, D. R., Schaefer, K. E., Chen, J. Y., De Visser, E. J., & Parasuraman, R. (2011). A meta-analysis of factors affecting trust in human-robot interaction. Human factors, 53(5), 517-527.
  • Sharkawy, A. N. (2021). Human-Robot Interaction: Applications. arXiv preprint arXiv:2102.00928.
  • Tsarouchi, P., Makris, S., & Chryssolouris, G. (2016). Human–robot interaction review and challenges on task planning and programming. International Journal of Computer Integrated Manufacturing, 29(8), 916-931.
  • Young, J. E., Sung, J., Voida, A., Sharlin, E., Igarashi, T., Christensen, H. I., & Grinter, R. E. (2011). Evaluating human-robot interaction. International Journal of Social Robotics, 3(1), 53-67.