A Multisensory and Support Vector Machine Based Teleoperate Robotic Arm

Abstract

Teleoperation is a crucial function for human-robotic cooperation. This paper presents an advanced multisensory controlling robotic arm based on flexible electromyography (EMG) sensor and inertial measurement unit (IMU). Signals from these sensors map to different degrees of freedom (DOFs) of the human body. And a support vector machine based algorithm process the data sampling from the sensors to classify three standard muscle modes. This method could reach a high accuracy of 98.7%. Through an adaptive control method based control algorithm, one user could use the robotic arm to finish one task with an average time of 37.6s. This article demonstrates a feasible means for robotic teleoperation by integrating multiple wearable sensing techniques and the comprehensive control algorithm, potentially advancing the development of human-robotic cooperation.