Title :
Joint visual attention modeling for naturally interacting robotic agents
Author :
Yucel, Z. ; Salah, Albert Ali ; Mericli, Cetin ; Mericli, T.
Author_Institution :
Electr. & Electron. Eng., Bilkent Univ., Ankara, Turkey
Abstract :
This paper elaborates on mechanisms for establishing visual joint attention for the design of robotic agents that learn through natural interfaces, following a developmental trajectory not unlike infants. We describe first the evolution of cognitive skills in infants and then the adaptation of cognitive development patterns in robotic design. A comprehensive outlook for cognitively inspired robotic design schemes pertaining to joint attention is presented for the last decade, with particular emphasis on practical implementation issues. A novel cognitively inspired joint attention fixation mechanism is defined for robotic agents.
Keywords :
humanoid robots; learning (artificial intelligence); man-machine systems; mobile robots; position control; robot vision; cognitive development patterns; cognitive skills; cognitively inspired joint attention fixation mechanism; cognitively inspired robotic design schemes; developmental trajectory; human-robot interaction; joint visual attention modeling; natural interfaces; naturally interacting robotic agents; robotic design; Frequency; Graphical models; Induction generators; Linear discriminant analysis; Performance gain; Robots; Statistics; Support vector machine classification; Support vector machines; Text categorization;
Conference_Titel :
Computer and Information Sciences, 2009. ISCIS 2009. 24th International Symposium on
Conference_Location :
Guzelyurt
Print_ISBN :
978-1-4244-5021-3
DOI :
10.1109/ISCIS.2009.5291820
