Title
Robot trajectory prediction and recognition based on a computational mirror neurons model
Abstract
Mirror neurons are premotor neurons that are considered to play a role in goal-directed actions, action understanding and even social cognition. As one of the promising research areas in psychology, cognitive neuroscience and cognitive physiology, understanding mirror neurons in a social cognition context, whether with neural or computational models, is still an open issue [5]. In this paper, we mainly focus on the action understanding aspect of mirror neurons, which can be regarded as a fundamental function of social cooperation and social cognition. Our proposed initial architecture is to learn a simulation of the walking pattern of a humanoid robot and to predict where the robot is heading on the basis of its previous walking trajectory.
Year
DOI
Venue
2011
10.1007/978-3-642-21738-8_43
ICANN (2)
Keywords
Field
DocType
understanding mirror neuron,cognitive physiology,robot trajectory prediction,social cooperation,mirror neuron,goal-directed action,cognitive neuroscience,social cognition context,action understanding,action understanding aspect,neurons model,social cognition,mirror neurons,recurrent neural network
Cognitive neuroscience,Mirror neuron,Computer science,Cognitive science,Recurrent neural network,Computational model,Artificial intelligence,Social cognition,Robot,Cognition,Machine learning,Humanoid robot
Conference
Volume
ISSN
Citations 
6792
0302-9743
2
PageRank 
References 
Authors
0.40
9
3
Name
Order
Citations
PageRank
Junpei Zhong1266.99
Cornelius Weber231841.92
Stefan Wermter31100151.62