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Robotics 2018, 7(3), 36;

Development of an EMG-Controlled Mobile Robot

Design Engineering and Mathematics Department, Middlesex University, London NW4 4BT, UK
Author to whom correspondence should be addressed.
Received: 22 May 2018 / Revised: 22 June 2018 / Accepted: 26 June 2018 / Published: 5 July 2018
PDF [4743 KB, uploaded 5 July 2018]


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. View Full-Text
Keywords: EMG; gesture recognition; k-NN classifier; Myo Armband; Robot Operating System (ROS) EMG; gesture recognition; k-NN classifier; Myo Armband; Robot Operating System (ROS)

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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).

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Bisi, S.; De Luca, L.; Shrestha, B.; Yang, Z.; Gandhi, V. Development of an EMG-Controlled Mobile Robot. Robotics 2018, 7, 36.

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