DocumentCode
1637859
Title
Is that me? Sensorimotor learning and self-other distinction in robotics
Author
Schillaci, Guido ; Hafner, Verena V. ; Lara, Bruno ; Grosjean, M.
Author_Institution
Cognitive Robot. Group, Humboldt-Univ. zu Berlin, Berlin, Germany
fYear
2013
Firstpage
223
Lastpage
224
Abstract
In order to have robots interact with other agents, it is important that they are able recognize their own actions. The research reported here relates to the use of internal models for self-other distinction. We demonstrate how a humanoid robot, which acquires a sensorimotor scheme through self-exploration, can produce and predict simple trajectories that have particular characteristics. Comparing these predictions to incoming sensory information provides the robot with a basic tool for distinguishing between self and other.
Keywords
humanoid robots; learning (artificial intelligence); mobile robots; Nao humanoid robot; robotics; self-other distinction; sensorimotor learning; sensorimotor scheme; sensory information; trajectory prediction; trajectory production; Inverse problems; Predictive models; Robot kinematics; Robot sensing systems; Training; Trajectory; Internal simulations; inverse and forward models; self-advantage; self-other distinction; sensorimotor learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Human-Robot Interaction (HRI), 2013 8th ACM/IEEE International Conference on
Conference_Location
Tokyo
ISSN
2167-2121
Print_ISBN
978-1-4673-3099-2
Electronic_ISBN
2167-2121
Type
conf
DOI
10.1109/HRI.2013.6483582
Filename
6483582
Link To Document