Title
Representation, Recognition and Generation of Actions in the Context of Imitation Learning
Abstract
The paper deals with the development of a cognitive architecture for learning by imitation in which a rich conceptual representation of the observed actions is built. We adopt the paradigm of conceptual spaces, in which static and dynamic entities are employed to efficiently organize perceptual data, to recognize positional relations, to learn movements from human demonstration and to generate complex actions by combining and sequencing simpler ones. The aim is to have a robotic system able to effectively learn by imitation and which has the capabilities of deeply understanding the perceived actions to be imitated. Experimentation has been performed on a robotic system composed of a PUMA 200 industrial manipulator and an anthropomorphic robotic hand.
Year
DOI
Venue
2006
10.1007/11681120_6
Springer Tracts in Advanced Robotics
Keywords
Field
DocType
cognitive architecture
Robot learning,Robotic hand,Computer science,Cognitive imitation,Imitative learning,Human–computer interaction,Artificial intelligence,Imitation,Cognitive architecture,Perception,Imitation learning,Machine learning
Conference
Volume
ISSN
Citations 
22
1610-7438
1
PageRank 
References 
Authors
0.38
3
2
Name
Order
Citations
PageRank
Haris Dindo112517.49
Ignazio Infantino215132.13