Concepts and methods to support the development and evaluation of remote collaboration using augmented reality

Abstract

Remote Collaboration using Augmented Reality (AR) shows great potential to establish a common ground in physically distributed scenarios where team-members need to achieve a shared goal. However, most research efforts in this field have been devoted to experiment with the enabling technology and propose methods to support its development. As the field evolves, evaluation and characterization of the collaborative process become an essential, but difficult endeavor, to better understand the contributions of AR. In this thesis, we conducted a critical analysis to identify the main limitations and opportunities of the field, while situating its maturity and proposing a roadmap of important research actions. Next, a human-centered design methodology was adopted, involving industrial partners to probe how AR could support their needs during remote maintenance. These outcomes were combined with literature methods into an AR-prototype and its evaluation was performed through a user study. From this, it became clear the necessity to perform a deep reflection in order to better understand the dimensions that influence and must/should be considered in Collaborative AR. Hence, a conceptual model and a human-centered taxonomy were proposed to foster systematization of perspectives. Based on the model proposed, an evaluation framework for contextualized data gathering and analysis was developed, allowing support the design and performance of distributed evaluations in a more informed and complete manner. To instantiate this vision, the CAPTURE toolkit was created, providing an additional perspective based on selected dimensions of collaboration and pre-defined measurements to obtain “in situ” data about them, which can be analyzed using an integrated visualization dashboard. The toolkit successfully supported evaluations of several team-members during tasks of remote maintenance mediated by AR. Thus, showing its versatility and potential in eliciting a comprehensive characterization of the added value of AR in real-life situations, establishing itself as a general-purpose solution, potentially applicable to a wider range of collaborative scenarios.