An Inertial Measurement Units and Electromyogram Based Control and Calibration Technique for Reducing Fatigue Issues in Teleoperations

Abstract

Teleoperation has been intensively used in diverse application scenarios in recent years. However, the frequently reported fatigue issue limits its successful use in tasks requiring long term and precise operations. One of key factors giving rise to the fatigue issue is the posture misalignment between the user’s arm and the robotic arm. Although conventional computer vision (CV) based solutions can implement postures alignment, they introduce potential privacy leakage problems at the same time. To address this issue, in this article we present an inertial measurement unit based technique for learning the posture status of the user’s arm and the robotic arm. Through a smart mapping algorithm, the proposed technique is proved to be a feasible manner to synchronize the two postures, potentially reducing the mental fatigue and preventing the privacy leakage possibilities.