DocumentCode :
2236411
Title :
Imitation based human-robot interaction - roles of joint attention and motion prediction
Author :
Akiwa, Yusuke ; Ogata, Tetsuya ; Suga, Yuki ; Sugano, Shigeki
Author_Institution :
Humanoid Robotics Instrum., Waseda Univ., Tokyo, Japan
fYear :
2004
fDate :
20-22 Sept. 2004
Firstpage :
283
Lastpage :
288
Abstract :
Behavior imitation is crucial for the acquisition of intelligence as well as in communication. This paper describes two kinds of experiments of human-robot communication based on behavior imitation. One compared the results obtained when the robot did and did not predict the experimental subject´s behaviors by using past datasets, and the other compared the results obtained with and without target objects in the simulator environment. The result of former experiment showed that the prediction of the subject´s behaviors increase the subject´s interest. The result of the latter experiment confirmed that the presence of objects facilitates joint attention and make human-robot communication possible even when the robot uses a simple imitation mechanism. This result shows that in human-robot communication, human not only recognizes the behaviors of the robot passively but also adapts to the situation actively. In conclusion, it is confirmed that the motion prediction and the presence of objects for joint attention are important for human-robot communication.
Keywords :
behavioural sciences computing; humanoid robots; man-machine systems; behavior imitation mechanism; human-robot communication; human-robot interaction; intelligence acquisition; joint attention; motion prediction; Aging; Human robot interaction; Humanoid robots; Informatics; Instruments; Intelligent robots; Predictive models; Robot kinematics; Robot sensing systems; Sections;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robot and Human Interactive Communication, 2004. ROMAN 2004. 13th IEEE International Workshop on
Print_ISBN :
0-7803-8570-5
Type :
conf
DOI :
10.1109/ROMAN.2004.1374774
Filename :
1374774
Link To Document :
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