Title :
Robots vs. machines: Identifying user perceptions and classifications
Author :
Schaefer, Kristin E. ; Billings, Deborah R. ; Hancock, Peter A.
Author_Institution :
Inst. for Simulation & Training, Univ. of Central Florida, Orlando, FL, USA
Abstract :
Ways in which people perceive machines as robots can influence their subsequent behavior and interactions. Individuals may make these classification decisions based solely on visual information, and thus the physical form of the entity alone. Participants viewed images of robots from a variety of identified domains and rated each image according to the extent to which they perceive the entity as a machine and the extent to which they viewed it as a robot. Findings suggest that images portraying greater anthropomorphic properties are classified as more robotic. Implications for robot design and trust are discussed.
Keywords :
human-robot interaction; anthropomorphic property; classification decision; machines; robot design; user behavior; user interaction; user perception; visual information; Educational institutions; Educational robots; Human factors; Humans; Service robots; Training; human-robot interaction; physical characteristics; robot appearance; robot classification;
Conference_Titel :
Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), 2012 IEEE International Multi-Disciplinary Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4673-0343-9
DOI :
10.1109/CogSIMA.2012.6188366