Paper Info
Title
Learning High-Level Manipulative Tasks through Imitation
Abstract
This paper presents ConSCIS, conceptual space based cognitive imitation system, which tightly links low-level data processing with knowledge representation in the context of robot imitation. Our focus is on the program-level imitation: we are interested in the final effects of actions on objects, and not on the particular kinematic or dynamic properties of the motion. The same architecture is used both to analyze and represent the task to be imitated, and to perform the imitation by generalizing in novel and different circumstances. The implemented experimental scenario is a two dimensional world populated with various objects in which observation/imitation takes place. To validate our approach, we report some results concerned with the problem of teaching a humanoid hand/arm robotic system tasks of assembling different workspace objects
Year
DOI
Venue
2006
10.1109/ROMAN.2006.314426
RO-MAN
Keywords
Field
DocType
cognitive systems,humanoid robots,knowledge representation,learning (artificial intelligence),conceptual space based cognitive imitation system,data processing,humanoid hand/arm robotic system,manipulative tasks learning,robot imitation,learning artificial intelligence
Computer vision,Knowledge representation and reasoning,Kinematics,Workspace,Computer science,Generalization,Cognitive imitation,Imitation,Artificial intelligence,Robot,Humanoid robot
Conference
ISBN
Citations 
PageRank 
1-4244-0565-3
2
0.38
References 
Authors
8
3
Name
Order
Citations
PageRank
Antonio Chella137465.74
Haris Dindo212517.49
I. Infantino3594.53