Preprint Article Version 1 This version is not peer-reviewed

Vision-driven collaborative robotic grasping system tele-operated by surface electromyography

Version 1 : Received: 27 June 2018 / Approved: 27 June 2018 / Online: 27 June 2018 (15:01:06 CEST)

A peer-reviewed article of this Preprint also exists.

Úbeda, A.; Zapata-Impata, B.S.; Puente, S.T.; Gil, P.; Candelas, F.; Torres, F. A Vision-Driven Collaborative Robotic Grasping System Tele-Operated by Surface Electromyography. Sensors 2018, 18, 2366. Úbeda, A.; Zapata-Impata, B.S.; Puente, S.T.; Gil, P.; Candelas, F.; Torres, F. A Vision-Driven Collaborative Robotic Grasping System Tele-Operated by Surface Electromyography. Sensors 2018, 18, 2366.

Journal reference: Sensors 2018, 18, 2366
DOI: 10.3390/s18072366

Abstract

This paper presents a system that merges computer vision and surface electromyography techniques to carry out grasping tasks. To perform this, the vision-driven system is used to compute pre-grasping poses of the robotic system based on the analysis of tridimensional object features. Then, the human operator can correct the pre-grasping pose of the robot using surface electromyographic signals from the forearm during wrist flexion and extension. Weak wrist flexions and extensions allow a fine adjustment of the robotic system to grasp the object and finally, when the operator considers that the grasping position is optimal, a strong flexion is performed to initiate the grasping of the object. The system has been tested with several subjects to check its performance showing a grasping accuracy of around 95% of the attempted grasps which increases by around a 9% the grasping accuracy of previous experiments in which electromyographic control was not implemented.

Subject Areas

surface electromyography; computer vision; grasping; assistive robotics

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