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    Information abstraction visualization for human-robot interaction

    Humphrey, Curtis Michael
    : https://etd.library.vanderbilt.edu/etd-07242009-091338
    http://hdl.handle.net/1803/13529
    : 2009-07-28

    Abstract

    Future emergency incident responses, including Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE), will incorporate robots. The ability to interact with robots and understand the resulting volumes of information requires a system of human-robot interfaces employing directable visualizations that provide information immediacy, relevancy, and sharing appropriate for each human’s responsibilities. This dissertation conducted two modified Cognitive Tasks Analyses (CTA) on the CBRNE incident response. The Cognitive Information Flow Analysis (CIFA) was developed to combine CTA results and to analyze the path of information as it passes through and is transformed by the system at different human-robot interaction (HRI) user levels. These analyses (i.e., modified CTAs and CIFA) collectively informed the HRI design and development. The primary contributions of this dissertation are the development and evaluation of two novel visualization techniques that present immediate, relevant, and shared information provided by the robots to the human users in the system of human-robot interfaces. The General Visualization Abstraction (GVA) algorithm, the first technique, is designed to provide information immediacy and relevancy by displaying the most useful information at any given moment determined by rewarding information that is either historically and currently relevant or novel and emerging. The Decision Information Abstracted to a Relevant Encapsulation (DIARE) concept, the second technique, supports decision-making by representing prior event information as a defined volume in the visualization’s information space and encapsulates the volume into an explicit and visual object that can be shared across time and users. User evaluations were conducted for both visualization techniques. The GVA algorithm’s evaluation results indicate that it can reduce cognitive workload, increase situational awareness, and improve performance for two different HRI user levels. The DIARE concept results indicate that participants were able to rapidly ascertain what had happened previously with great accuracy and good memory recall. Together, these two visualization techniques can assist decision-makers using directable visualizations, such as those used in HRI, by offering an effective method of sharing and providing real-time, relevant information.
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