Národní úložiště šedé literatury Nalezeno 2 záznamů.  Hledání trvalo 0.00 vteřin. 
Human-Robot Interaction: Advanced Task-centered Interfaces for Non-Expert Users
Materna, Zdeněk ; Ao.Univ.Prof. Dipl.-Ing. Dr.tech Markus Vincze (oponent) ; Míkovec, Zdeněk (oponent) ; Smrž, Pavel (vedoucí práce)
Recent years brought a growing trend of deploying robots in novel applications where they are not only supposed to co-exist with and work next to humans but to actually closely collaborate with them on shared complex tasks. Capabilities of the robotic systems need to be substantially expanded in order to make the close, rich as well as natural human-robot interaction possible. Indeed, the interaction will not only happen between caged robots and highly specialized experts any more. More and more often, it will interconnect safe and interactive robots with non-expert users with various background. Consequently, the amazingly complex machines, that the current robots are, will become even more complex. This poses further challenges for the design of their user interfaces. The objective of this thesis is to research and develop solutions for the close interaction between non-expert users and complex robots. The research was done in two different contexts: assistive service and industrial collaborative robots. Although these two domains have diverse requirements, related concepts could be used when designing the human-robot interaction. To cope with limitations of the current approaches, a novel method for task-centered interaction has been proposed. The most important aspects of the method are the utilization of mixed reality and robot-integrated capabilities, communication of the robot's inner state, context sensitivity, and usage of task-appropriate modalities. For each of the two mentioned domains, a user interface was designed and implemented. Both interfaces were successfully evaluated with non-expert users, who were able to carry out non-trivial tasks in cooperation with a robot. The reported evaluation provides an evidence that the realized method significantly improves the close human-robot interaction, which had not been entirely possible with previous approaches. The method's key characteristics provide guidelines for new designs of next user interfaces in the collaborative robotics.
Multimedia Data Processing in Heterogeneous Distributed Environment
Kajan, Rudolf ; Ferko,, Andrej (oponent) ; Míkovec, Zdeněk (oponent) ; Herout, Adam (vedoucí práce)
Ubiquitous computing, a paradigm in which the processing of information is linked with each activity or object as encountered, was proposed by Mark Weiser as the next era for interacting with computers. Its goal is to enable people to interact with devices more naturally and casually in ways that suit whatever location or context they find themselves in. Ubiquitous computing focuses on learning by removing the complexity of computing and increases efficiency while using computing for different daily activities. But after more than 15 years since Weiser formulated these goals, several aspects of ubiquitous computing are still not a part of user experience with today’s technology. Seamless integration with environment leading to technological invisibility or user interaction spanning across multiple devices pose still a great challenge. The main goal of our work is to make a step towards making the idea of ubiquitous computing a reality by addressing the question about intuitive information sharing between a personal device and a situated display. We have developed three interaction techniques which support unobtrusive content exchange between touch-enabled personal device and a large display - whether it is shared-private or public. These techniques are based on video streams, augmented reality, and analysis of gaze data. Besides the interaction techniques, we also present a framework for real-time application state acquisition and reconstruction on target platform. We report on user studies focused on the usability of our prototypes and a system performance evaluations. Our experiments were formed around real-life scenarios which are commonly experienced throughout the day. For interactions based on video streams, the results indicate that our techniques outperform the existing solutions: the localization and task migration is done in real time on a midlevel cellphone; the localization is reliable even for different observation angles and for cluttered screen content. Our technique based on gaze analysis goes even further by allowing for modeling of implicit user preferences through gaze data, while being accurate and unobtrusive.

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