6533b872fe1ef96bd12d3112
RESEARCH PRODUCT
A Posture Sequence Learning System for an Anthropomorphic Robotic Hand
Haris DžindoIgnazio InfantinoIrene MacalusoAntonio ChellaAntonio Chellasubject
Visual perceptionHand posture recognitionComputer scienceMachine visionGeneral Mathematicsmedia_common.quotation_subjectHuman–computer interfaceHuman-computer interfaceRobotics; Imitation learning; Machine learningHuman–computer interactionPerceptionMachine learningComputer visionConceptual spacesmedia_commonConceptual spaceSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryVisual perceptionImitation learningRepresentation (systemics)CognitionCognitive architectureComputer Science ApplicationsRoboticControl and Systems EngineeringSequence learningArtificial intelligencebusinessSoftwareGesturedescription
The paper presents a cognitive architecture for posture learning of an anthropomorphic robotic hand. Our approach is aimed to allow the robotic system to perform complex perceptual operations, to interact with an human user and to integrate the perceptions by a cognitive representation of the scene and the observed actions. The anthropomorphic robotic hand imitates the gestures acquired by the vision system in order to learn meaningful movements, to build its knowledge by different conceptual spaces and to perform complex interaction with the human operator.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2003-01-01 |