This paper describes initial validation of a theoretical framework to support research on the visualization of uncertainty. Two experiments replicated and extended this framework, illustrating how the manipulation of task complexity produces differences in performance. Additionally, using a combinatory metric of workload and performance, this framework provides a new metric for assessing uncertainty visualization. We describe how this work acts as a theoretical scaffold for examining differing forms of visualizations of uncertainty by providing a means for systematic variations in task context.
This study investigated how humans interact socially with robots. Participants engaged in a hallway navigation task with a robot. Throughout twelve trials, the display on the robot and its proxemics behavior was varied while participants were tasked with first, reacting to the robot’s actions and second, interpreting its behavior. Results indicated that proxemic behavior and robotic display characteristics influence the degree to which individuals perceive the robot as socially present, with more human-like displays and assertive robotic behaviors resulting in greater assessments of social presence. When examined in isolation, repeated interactions over time do not appear to affect the perception of a socially present robot under these particular circumstances. Results are discussed in the context of how social signals theory inform research in human-robot interaction.
One day in the future, robots will become a normal feature of everyday life and effective human-robotic partnerships will be important. The purpose of the present study was to identify the impact certain social design elements have on likability and fear in human-robot interactions through examination of human-like feminine, human-like masculine, human-like gender-neutral, and machine-like robots. The current study examined college students at a small private university. Analyses revealed that robot appearance did influence likability, with the human-like gender-neutral robot liked most by participants. Robot appearance also played a role in shaping evaluations of fear, with the human-like feminine robot feared more than the human-like gender-neutral and machine-like robots, but no more than the human-like masculine robot. The discussion centers on the importance of studying likability and fear in the context of HRI.
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