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Dynamic time warping–based feature selection method for foot gesture cobot operation mode selection

Tchane Djogdom Gilde Vanel, Otis Martin J.-D. et Meziane Ramy. (2023). Dynamic time warping–based feature selection method for foot gesture cobot operation mode selection. The International Journal of Advanced Manufacturing Technology, 126, (9-10), p. 4521-4541.

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The emerging needs of human beings are pushing manufacturing companies from mass production to mass customization. The occurrence of these new challenges leads to a change of scenario where the robot no longer works isolated from human to a scenario in which the robot collaborates with the human in the same workspace (collaborative robotics). Wearable sensors using inertial measurement unit (IMU) are widely used to capture human upper body gestures in which the set of gesture being recognize is very large. However, foot gesture approach is starting to gain some places in applications where human’s hands are occupied when interacting with robots. This study presents an insole-based foot gesture recognition method for cobot operation mode selection. The insole is composed of an IMU and four force sensors. The classification algorithm uses a support vector machine (SVM) classifier based on features extracted by means of dynamic time warping (DTW) applied to only one reference gesture signal. Five human participants are used for the dataset. As a case study, the system was interfaced in real time (real-time classification algorithm) using a Simulink 2020a scheme with Universal Robots UR5 (5 kg payload). The worst-case recognition accuracy is around 88%. The algorithm is able to adequately discriminate between 10-foot gestures by means of a wearable insole sensor incorporated into the insole. Moreover, this study shows that, the control gesture can accurately be recognized from other current activities such as walking, turning, climbing the stairs, and similar.

Type de document:Article publié dans une revue avec comité d'évaluation
Pages:p. 4521-4541
Version évaluée par les pairs:Oui
Date:Avril 2023
Identifiant unique:10.1007/s00170-023-11280-w
Sujets:Sciences naturelles et génie > Génie
Sciences naturelles et génie > Génie > Génie informatique et génie logiciel
Sciences naturelles et génie > Sciences appliquées
Département, module, service et unité de recherche:Départements et modules > Département des sciences appliquées > Module d'ingénierie
Unités de recherche > Laboratoire d’automatique et de robotique interactive (LAR.i)
Mots-clés:human-robot collaboration, instrumented insole, foot gesture recognition, support vector machine, dynamic time warping, collaboration homme-robot, semelle intérieure instrumentée, reconnaissance des gestes du pied, machine à vecteur de support, déformation temporelle dynamique
Déposé le:07 juin 2023 17:49
Dernière modification:20 avr. 2024 04:00
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