Tracking Control Properties of Human–Robotic Systems Based on Impedance Control
neural network (NN)
Human–robotic systems that include interaction betweenhuman operators and robots should be designed with carefulconsideration for the dynamic property and control ability of ahuman operator. This paper performs manual tracking controltests on a human–robotic system using an impedance-controlledrobot, and investigates control characteristics of a human operatoraccording to the robot impedance properties. Experimental resultsdemonstrate that humans try to maintain dynamic properties ofan overall system as constant as possible by adjusting their ownimpedance properties. Then, a new training system using a neuralnetwork for operating a human–robotic system is constructedon the basis of the experimental findings in the human trackingcontrol properties.
IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans
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Graduate School of Engineering