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This paper has developed a coordination control method for a dual-arm exoskeleton robot based on human impedance transfer skills, where the left (master) robot arm extracts the human limb impedance stiffness and position profiles, and then transfers the information to the right (slave) arm of the exoskeleton. A computationally efficient model of the arm endpoint stiffness behavior is developed and a co-contraction index is defined using muscular activities of a dominant antagonistic muscle pair. A reference command consisting of the stiffness and position profiles of the operator is computed and realized by one robot in real-time. Considering the dynamics uncertainties of the robotic exoskeleton, an adaptive-robust impedance controller in task space is proposed to drive the slave arm tracking the desired trajectories with convergent errors. To verify the robustness of the developed approach, a study of combining adaptive control and human impedance transfer control under the presence of unknown interactive forces is conducted. The experimental results of this paper suggest that the proposed control method enables the subjects to execute a coordination control task on a dual-arm exoskeleton robot by transferring the stiffness from the human arm to the slave robot arm, which turns out to be effective

Coordination Control of a Dual-Arm Exoskeleton Robot Using Human Impedance Transfer Skills