Is That Me? Sensorimotor Learning and Self-Other Distinction in Robotics

被引:0
|
作者
Schillaci, Guido [1 ]
Hafner, Verena V. [1 ]
Lara, Bruno [2 ]
Grosjean, Marc [3 ]
机构
[1] Humboldt Univ, Cognit Robot Grp, Berlin, Germany
[2] Univ Autonama Estab Morelos, Cuernavaca, Morelos, Mexico
[3] Leibniz Res Ctr Working Environm & Human Factors, Dortmund, Germany
来源
PROCEEDINGS OF THE 8TH ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION (HRI 2013) | 2013年
关键词
Internal simulations; inverse and forward models; self-advantage; self-other distinction; sensorimotor learning; PERCEPTION;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:223 / +
页数:2
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