6533b853fe1ef96bd12ac1b7
RESEARCH PRODUCT
A Cognitive Framework for Imitation Learning
Antonio ChellaIgnazio InfantinoHaris Dindosubject
Computer sciencebusiness.industryMovement (music)General Mathematicsmedia_common.quotation_subjectImitationlearningRepresentation (systemics)Cognitive architectureCognitive roboticsRobotics Imitation LearningIntelligent manipulationComputer Science ApplicationsControl and Systems EngineeringPerceptionConceptual spacesArtificial intelligenceCognitive imitationImitationbusinessCognitive roboticsSoftwaremedia_commondescription
Abstract In order to have a robotic system able to effectively learn by imitation, and not merely reproduce the movements of a human teacher, the system should have the capabilities of deeply understanding the perceived actions to be imitated. This paper deals with the development of cognitive architecture for learning by imitation in which a rich conceptual representation of the observed actions is built. The purpose of the following discussion is to show how this Conceptual Area can be employed to efficiently organize perceptual data, to learn movement primitives from human demonstration and to generate complex actions by combining and sequencing simpler ones. The proposed architecture has been tested on a robotic system composed of a PUMA 200 industrial manipulator and an anthropomorphic robotic hand.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2006-05-01 |