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Shared control methodology based on head positioning and vector fields for people with quadriplegia

Published online by Cambridge University Press:  20 May 2021

Guilherme M. Maciel ,
Milena F. Pinto Open the ORCID record for Milena F. Pinto [Opens in a new window] ,
Ivo C. da S. Júnior ,
Fabricio O. Coelho ,
Andre L. M. Marcato Open the ORCID record for Andre L. M. Marcato [Opens in a new window]  and
Marcelo M. Cruzeiro
Guilherme M. Maciel*
Affiliation:
Department of Electrical Engineering, Federal University of Juiz de Fora (UFJF), Juiz de Fora, Brazil
Milena F. Pinto
Affiliation:
Department of Electronics, Federal Center for Technological Education of Rio de Janeiro (CEFET-RJ), Rio de Janeiro, Brazil
Ivo C. da S. Júnior
Affiliation:
Department of Electrical Engineering, Federal University of Juiz de Fora (UFJF), Juiz de Fora, Brazil
Fabricio O. Coelho
Affiliation:
Department of Electrical Engineering, Federal University of Juiz de Fora (UFJF), Juiz de Fora, Brazil
Andre L. M. Marcato
Affiliation:
Department of Electrical Engineering, Federal University of Juiz de Fora (UFJF), Juiz de Fora, Brazil
Marcelo M. Cruzeiro
Affiliation:
Department of Clinical Medicine, Federal University of Juiz de Fora (UFJF), Juiz de Fora, Brazil
*
*Corresponding author. Email: guilherme.marins@engenharia.ufjf.br
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Abstract

Mobile robotic systems are used in a wide range of applications. Especially in the assistive field, they can enhance the mobility of the elderly and disable people. Modern robotic technologies have been implemented in wheelchairs to give them intelligence. Thus, by equipping wheelchairs with intelligent algorithms, controllers, and sensors, it is possible to share the wheelchair control between the user and the autonomous system. The present research proposes a methodology for intelligent wheelchairs based on head movements and vector fields. In this work, the user indicates where to go, and the system performs obstacle avoidance and planning. The focus is developing an assistive technology for people with quadriplegia that presents partial movements, such as the shoulder and neck musculature. The developed system uses shared control of velocity. It employs a depth camera to recognize obstacles in the environment and an inertial measurement unit (IMU) sensor to recognize the desired movement pattern measuring the user’s head inclination. The proposed methodology computes a repulsive vector field and works to increase maneuverability and safety. Thus, global localization and mapping are unnecessary. The results were evaluated by simulated models and practical tests using a Pioneer-P3DX differential robot to show the system’s applicability.

Keywords

shared controlvector fieldsmobile robotshead positioningquadriplegia
Type
Article
Information
Robotica , Volume 40 , Issue 2 , February 2022 , pp. 348 - 364
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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