Development of an EMG-controlled mobile robot

Article


Bisi, S., De Luca, L., Shrestha, B., Yang, Z. and Gandhi, V. 2018. Development of an EMG-controlled mobile robot. Robotics. 7 (3), pp. 1-13. https://doi.org/10.3390/robotics7030036
TypeArticle
TitleDevelopment of an EMG-controlled mobile robot
AuthorsBisi, S., De Luca, L., Shrestha, B., Yang, Z. and Gandhi, V.
Abstract

This paper presents the development of a Robot Operating System (ROS)-based mobile robot control using electromyography (EMG) signals. The proposed robot’s structure is specifically designed to provide modularity and is controlled by a Raspberry Pi 3 running on top of an ROS application and a Teensy microcontroller. The EMG muscle commands are sent to the robot with hand gestures that are captured using a Thalmic Myo Armband and recognized using a k-Nearest Neighbour (k-NN) classifier. The robot’s performance is evaluated by navigating it through specific paths while solely controlling it through the EMG signals and using the collision avoidance approach. Thus, this paper aims to expand the research on the topic, introducing a more accurate classification system with a wider set of gestures, hoping to come closer to a usable real-life application

KeywordsEMG; gesture recognition; k-NN classifier; Myo Armband; Robot Operating System (ROS)
PublisherMDPI AG
JournalRobotics
ISSN2218-6581
Publication dates
Online05 Jul 2018
PrintSep 2018
Publication process dates
Submitted22 May 2018
Accepted26 Jun 2018
Deposited07 Jun 2019
Output statusPublished
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Copyright Statement

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Digital Object Identifier (DOI)https://doi.org/10.3390/robotics7030036
Web of Science identifierWOS:000445185400005
LanguageEnglish
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Franca, F. and Yang, Z. 2000. Building artificial CPGs with asymmetric Hopfield networks. The IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2000). Como, Italy 24 - 27 Jul 2000
Generating arbitrary rhythmic patterns with purely inhibitory neural networks
Yang, Z. and Franca, F. 1998. Generating arbitrary rhythmic patterns with purely inhibitory neural networks. in: Verleysen, M. (ed.) ESANN'1998 proceedings - 6th European symposium on artificial neural networks (Bruges, 22-23-24 April 1998) D facto. pp. 53-58