Journal
Scientific and technical journal «Priborostroenie»
UDK007.51
Issue:10 (67)
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VARIABLE IMPEDANCE LEARNING CONTROL FOR ROBOTIC ARMS FROM GMR-ENCODED BEHAVIOR PRIORS
Annotation
This study presents a control approach, where Cartesian variable impedance control parameters are tuned online as the result of quadratic programming optimization dynamically modulating stiffness and damping coefficients based on desired sensory-motor skill encoded by Gaussian mixture regression behavior prior model.
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