Search results for "Imitation learning"

showing 6 items of 16 documents

A Posture Sequence Learning System for an Anthropomorphic Robotic Hand

2003

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.

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 intelligencebusinessSoftwareGesture
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An adaptive probabilistic approach to goal-level imitation learning

2010

Imitation learning has been recognized as a promising technique to teach robots advanced skills. It is based on the idea that robots could learn new behaviors by observing and imitating the behaviors of other skilled actors. We propose an adaptive probabilistic graphical model which copes with three core issues of any imitative behavior: observation, representation and reproduction of skills. Our model, Growing Hierarchical Dynamic Bayesian Network (GHDBN), is hierarchical (i.e. able to characterize structured behaviors at different levels of abstraction), and growing (i.e. skills are learned or updated incrementally - and at each level of abstraction - every time a new observation sequence…

business.industryComputer scienceProbabilistic logicMachine learningcomputer.software_genreRobotArtificial intelligenceGraphical modelRobotics Imitation Learning Machine Learning Bayesian ModelsbusinessRepresentation (mathematics)Hidden Markov modelcomputerDynamic Bayesian networkHumanoid robotAbstraction (linguistics)2010 IEEE/RSJ International Conference on Intelligent Robots and Systems
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An adaptive probabilistic graphical model for representing skills in PbD settings

2010

business.industryComputer scienceProgramming by demonstrationBayesian probabilityProbabilistic logicMachine learningcomputer.software_genreUnsupervised learningArtificial intelligenceGraphical modelMachine Learning Imitation Learning Incremental Learning Dynamic Bayesian Network Growing Hierarchical Dynamic Bayesian NetworkAutomatic programmingbusinessHidden Markov modelcomputerDynamic Bayesian network
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Anchoring by Imitation Learning in Conceptual Spaces

2005

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 a 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 the same conceptual representation can be used both in a bottom-up approach, in order to learn sequences of actions by imitation learning paradigm, and in a top-down approach, in order to anchor the symbolical representations to the perceptu…

business.industryComputer sciencemedia_common.quotation_subjectRepresentation (systemics)RoboticsCognitive architectureRobotics Imitation learningHuman–computer interactionPerceptionCognitive developmentArtificial intelligenceCognitive imitationImitationbusinessSet (psychology)media_common
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A Cognitive Architecture for Robotic Hand Posture Learning

2005

This paper deals with the design and implementation of a visual control of a robotic system composed of a dexterous hand and video camera. The aim of the proposed system is to reproduce the movements of a human hand in order to learn complex manipulation tasks or to interact with the user. A novel algorithm for robust and fast fingertips localization and tracking is presented. A suitable kinematic hand model is adopted to achieve a fast and acceptable solution to an inverse kinematics problem. The system is part of a cognitive architecture for posture learning that integrates the perceptions by a high-level representation of the scene and of the observed actions. The anthropomorphic robotic…

imitation learningInverse kinematicsgesture recognitionbusiness.industryMachine visionComputer scienceCognitive architectureKinematicsAnthropometryCognitive architectureHuman–robot interactionComputer Science ApplicationsHuman-Computer Interactionrobotic visionControl and Systems EngineeringGesture recognitionRobot handComputer visionArtificial intelligenceElectrical and Electronic Engineeringbusinesshuman-robot interfaceSoftwareInformation SystemsGesture
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Humanoid Cognitive Robots That Learn by Imitating: Implications for Consciousness Studies.

2018

While the concept of a conscious machine is intriguing, producing such a machine remains controversial and challenging. Here we describe how our work on creating a humanoid cognitive robot that learns to perform tasks via imitation learning relates to this issue. Our discussion is divided into three parts. First, we summarize our previously-detailed framework for advancing the understanding of the nature of phenomenal consciousness. This framework is based on identifying computational correlates of consciousness. Second, we describe a cognitive robotic system that we recently developed that learns to perform tasks by imitating human-provided demonstrations. This humanoid robot uses cause-ef…

imitation learningartificial consciousnessComputer sciencemedia_common.quotation_subjectlcsh:Mechanical engineering and machinerymachine consciousnessArtificial consciousnesscognitive phenomenology050105 experimental psychologylcsh:QA75.5-76.95working memory03 medical and health sciences0302 clinical medicineArtificial Intelligence0501 psychology and cognitive scienceslcsh:TJ1-1570cognitive robotsmedia_commonOriginal ResearchCognitive scienceRobotics and AIWorking memory05 social sciencesCognitioncomputational explanatory gapComputer Science Applicationsneural network gating mechanismsRobotCausal reasoninglcsh:Electronic computers. Computer scienceConsciousnessNeurocognitive030217 neurology & neurosurgeryHumanoid robotFrontiers in robotics and AI
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