Learning parametric dynamic movement primitives from multiple demonstrations

Neural Networks

Volumn 24, Issue 5, 2011, Pages 493-500

  Matsubara, Takamitsu ^a,b   Hyon, Sang Ho ^a,c   Morimoto, Jun ^b  

^a NARA INSTITUTE OF SCIENCE AND TECHNOLOGY   (Japan)

^b ADVANCED TELECOMMUNICATIONS RESEARCH INSTITUTE INTERNATIONAL   (Japan)

^c RITSUMEIKAN UNIVERSITY   (Japan)

Author keywords

Imitation learning; Motion styles; Movement primitives

Indexed keywords

COMMON FACTORS; DUAL-ARM ROBOT; DYNAMIC MOVEMENT PRIMITIVES; IMITATION LEARNING; LEARNING CONTROL; LEARNING FROM DEMONSTRATION; LEARNING PROCEDURES; LINEAR COEFFICIENTS; MOTION STYLES; MOVEMENT PRIMITIVES; MOVEMENT SKILLS; PARAMETER VECTORS; REAL ENVIRONMENTS; RHYTHMIC MOVEMENTS; STABILITY AND ROBUSTNESS; USEFUL PROPERTIES;

DIFFERENTIAL EQUATIONS; SCALABILITY;

DEMONSTRATIONS;

ARM MOVEMENT; ARTICLE; BEHAVIORAL SCIENCE; BODY MOVEMENT; CONCEPTUAL FRAMEWORK; CONTROLLED STUDY; DYNAMIC MOVEMENT PRIMITIVE; HUMAN; HUMAN EXPERIMENT; LEARNING ALGORITHM; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MOTOR SYSTEM; PARAMETRIC TEST; PRIORITY JOURNAL; PROCESS DESIGN; PROCESS DEVELOPMENT; ROBOTICS; SYSTEM ANALYSIS; WALKING;

ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; HUMANS; IMITATIVE BEHAVIOR; MATHEMATICAL CONCEPTS; MODELS, THEORETICAL; MOTION PERCEPTION; MOTOR SKILLS; MOVEMENT; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; ROBOTICS; SOFTWARE; SOFTWARE DESIGN;

EID: 79953692970     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2011.02.004     Document Type: Article

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