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In this letter, we propose a control strategy for human-robot cooperative manipulation under the ambiguous collaboration of a human agent. To cope with this uncertainty, an adaptive update law inferring… Click to show full abstract
In this letter, we propose a control strategy for human-robot cooperative manipulation under the ambiguous collaboration of a human agent. To cope with this uncertainty, an adaptive update law inferring the human contribution to the system dynamics from basic perception feedback through the human arm stiffness is used. Furthermore, the robustness and accuracy of the approach is enhanced by redundantly tracking the shared load references and its associated end-effector position references. To validate the control strategy, both theoretical Lyapunov stability analysis and experimental results –employing two robot manipulators with 6 degrees of freedom under external disturbances– are provided.
Journal Title: IEEE Robotics and Automation Letters
Year Published: 2022
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