@PhdThesis{duepublico_mods_00076145,
  author = 	{Arntz, Alexander},
  title = 	{Meet Your Robotic Work Colleague: Exploring Human-Robot Collaboration in a Virtual Reality based Research Platform},
  year = 	{2022},
  month = 	{Jun},
  day = 	{30},
  keywords = 	{Human-Robot Collaboration},
  abstract = 	{Autonomous robots, capable of collaborating with humans could benefit industrial production by supporting personnel in domains with tedious, repetitive, and dangerous tasks. To make this vision reality, Human-Robot Collaboration (HRC) has established itself as a research field. HRC researchers identified multiple challenges regarding the technical implementation such as enabling the robot to act autonomously, as well as human factors aspects, e.g., expectation conformity. These challenges prevent current realizations of industrial processes involving the collaboration between humans and robots to reach their full potential. Due to the variety of robot representations and shared task requirements, extensive research is needed to develop solutions to overcome these challenges. However, confronting these challenges in empirical studies is restricted due to safety concerns as exposing participants to prototypical implementations of robot collaboration setups either in full contact or close proximity can provoke hazardous situations. To address this problem, this research presented here proposes a virtual reality (VR) application, where new concepts for HRC configurations can be explored and tested without causing harm to participants. Due to the nature of VR, the application can function as a sandbox, where a wide range of HRC settings can be portrayed without the need for expensive and elaborate setups involving real robots. The design and functionality of the VR application were developed in accordance with the state-of-the-art HRC research literature, established statutory norms, and remarks from industry representatives. The VR application offers several features, such as the implementation of machine learning agents in conjunction with an inverse kinematic system that allows the virtual representation of an autonomous robot to collaborate with a human participant on a designated shared task. The versatility of the VR application allows for the creation of multiple forms of stimulus materials depending on the requirements of the study, ranging from interactive setups, where participants collaborated with the robot within the virtual environment, and passive media, such as videos and images. Additionally, every parameter within the virtual environment can be adjusted to fit the targeted scenario. By using this VR application, a series of three experimental studies with 80 participants addressed the challenges of HRC by exploring various effects of augmenting an autonomous robot with communication in collaboration scenarios. In addition, two qualitative studies were conducted to complement the research on positive and negative impressions of the robot. Considering that communication is a substantial contributor to the success of collaboration among humans, it is assumed that it benefits HRC as well. However, research is still open to finding an effective arrangement, due to the countless variations of HRC setups that are difficult to recreate in a lab environment. In addition to the effect of the communication, derived from the challenges of HRC selected human factors variables, such as perceived stress as well as the overall perception of the robot as an intelligent system, were collected due to their potential to affect the collaboration process. To complement the subjective data from the questionnaire, the VR application collected objective data, e.g., the collision frequency and production quantity to investigate the safety and task allocation challenges of HRC. The qualitative and quantitative results from the conducted empirical studies in this dissertation revealed several benefits regarding the usage of communication in HRC scenarios. The communication of contextual information in form of guidance for the shared task and explanation of the robot's actions, among other aspects, reduced the perceived stress, improved the overall perception of the robot, and induced the impression of the robot as an intelligent system. While these studies merely confronted a fraction of the vast challenges of HRC, the results provide a foundation for future design decisions regarding the implementation of industrial HRC scenarios involving autonomous robots. In addition to the results of the empirical studies, a key contribution of this work is the VR application that can be used as a tool to investigate a wide variety of HRC scenarios. The VR application itself provides a platform that can be continuously expanded and used for future studies exploring HRC concepts difficult to evaluate otherwise. Through this VR application, the goal is to contribute to the efforts of the HRC research community to develop a common methodology for the collaboration between humans and robots in industrial environments.},
  doi = 	{10.17185/duepublico/76145},
  url = 	{https://duepublico2.uni-due.de/receive/duepublico_mods_00076145},
  url = 	{https://doi.org/10.17185/duepublico/76145},
  file = 	{:https://duepublico2.uni-due.de/servlets/MCRFileNodeServlet/duepublico_derivate_00075871/Diss_Arntz.pdf:PDF},
  language = 	{en}
}