Authors:
Vladislav Berezhnoy
;
Dmitry Popov
;
Ilya Afanasyev
and
Nikolaos Mavridis
Affiliation:
Institute of Robotics, Innopolis University, Universitetskaya Str. 1, Innopolis, 420500 and Russia
Keyword(s):
Gesture-based Control Interface, Glove System, Fuzzy C-means (FCM) Clustering, Arduino, V-REP Simulator.
Related
Ontology
Subjects/Areas/Topics:
Control and Supervision Systems
;
Human-Machine Interfaces
;
Human-Robots Interfaces
;
Informatics in Control, Automation and Robotics
;
Perception and Awareness
;
Robotics and Automation
;
Telerobotics and Teleoperation
Abstract:
The paper presents an approach to building a gesture-based control interface with a wearable glove system and a real-time gesture recognition algorithm. The glove-based system is a wireless wearable device with hardware components, including Arduino Nano controller, IMU and flex sensors, and software for gesture recognition. Our gesture recognition methodology requires two stages: 1) Building a library of dynamic gesture models with the reference human gesture graphs; 2) Gesture capturing and evaluating with fuzzy c-means (FCM) clustering and constructing grammars of gestures by fuzzy membership functions. The system tests were provided with 6 different dynamic gestures to control position and orientation of a quadcopter in V-Rep simulator that has demonstrated encouraging results with a reasonable quality of real-time gesture-based quadcopter control.