In our modern and computer-driven environment the topic of Human Computer Interaction becomes more important, in order to design efficient and flexible interfaces. A field of increasing importance is Augmented Reality, where current interaction techniques and principles are not yet satisfying or sufficient for the great potential of these technologies. Especially haptic feedback during user interaction is an important and complex topic. With the ACTO system, Vonach et al. developed a Tangible User Interface (TUI) for prototyping haptic interfaces. In this thesis we use this system to provide haptic interaction for Augmented Reality (AR). Therefore we first developed an alternative tracking system for the ACTO robots, called TrACTOr. With this new tracking solution we want to overcome some shortcomings of the existing tracking solution, as well as fit the needs of an AR application better. Based on the new tracking system we implemented an AR based learning application with haptic user interaction, called StARboard. With StARboard we wanted to investigate the benefits of haptic interaction for learning systems for the users. We present the concepts of the tracking solution and the learning application. The development of additional hardware for the ACTO robots, as well as the system setup is explained. Also the implementation of TrACTOr and StARboard is discussed in detail. The technical evaluation of the system showed that the TrACTOr tracking system has a high enough performance and accuracy to provide real time tracking data for an AR based application. The user evaluation we performed with the implemented system showed that for learning systems, haptic interaction in combination with AR can match the performance of conventional desktop applications or gesture based AR applications. The users rated this new interaction technique as very intuitive, fast and easy to use.
C. Schindler: "TrACTOr & StARboard Tracking and Haptic Interaction for Learning in AR"; Supervisor: H. Kaufmann, E. Vonach; Institute for Visual Computing and Human-Centered Technology, 2018; final examination: 10-04-2018.
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