Hand Gesture Interface to Teach an Industrial Robots

Mojtaba Khanesar, David Branson

2023

Abstract

The present paper proposes user gesture recognition to control industrial robots. To recognize hand gestures, MediaPipe software package and an RGB camera is used. The proposed communication approach is an easy and reliable approach to provide commands for industrial robots. The landmarks which are extracted by MediaPipe software package are used as the input to a gesture recognition software to detect hand gestures. Five different hand gestures are recognized by the proposed machine learning approach in this paper. Hand gestures are then translated to movement directions for the industrial robot. The corresponding joint angle updates are generated using damped least squares inverse kinematic approach to move the industrial robot in a plane. The motion behaviour of the industrial robot is simulated within V-REP simulation environment. It is observed that the hand gestures are communicated with high accuracy to the industrial robot and the industrial robot follows the movements accurately.

Paper Citation

in Harvard Style

Khanesar M. and Branson D. (2023). Hand Gesture Interface to Teach an Industrial Robots. In Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-670-5, SciTePress, pages 243-249. DOI: 10.5220/0012205200003543

in Bibtex Style

@conference{icinco23,
author={Mojtaba Khanesar and David Branson},
title={Hand Gesture Interface to Teach an Industrial Robots},
booktitle={Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2023},
pages={243-249},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012205200003543},
isbn={978-989-758-670-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Hand Gesture Interface to Teach an Industrial Robots
SN - 978-989-758-670-5
AU - Khanesar M.
AU - Branson D.
PY - 2023
SP - 243
EP - 249
DO - 10.5220/0012205200003543
PB - SciTePress