Sensitivity Based Selection of an Optimal Cable-Driven Parallel Robot Design for Rehabilitation Purposes

This paper deals with the design of an optimal cable-driven parallel robot (CDPR) for upper limb rehabilitation. The robot’s prescribed workspace is identified with the help of an occupational therapist based on three selected daily life activities, which are tracked using a Qualisys motion capture...

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Main Authors: Ferdaws Ennaiem, Abdelbadiâ Chaker, Juan Sebastián Sandoval Arévalo, Med Amine Laribi, Sami Bennour, Abdelfattah Mlika, Lotfi Romdhane, Saïd Zeghloul
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Robotics
Subjects:
Online Access:https://www.mdpi.com/2218-6581/10/1/7
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spelling doaj-8c691d7d095d42ffb3bb42e17712d1b02021-01-01T00:03:29ZengMDPI AGRobotics2218-65812021-12-01107710.3390/robotics10010007Sensitivity Based Selection of an Optimal Cable-Driven Parallel Robot Design for Rehabilitation PurposesFerdaws Ennaiem0Abdelbadiâ Chaker1Juan Sebastián Sandoval Arévalo2Med Amine Laribi3Sami Bennour4Abdelfattah Mlika5Lotfi Romdhane6Saïd Zeghloul7Department of GMSC, Prime Institute CNRS, ENSMA, University of Poitiers, UPR 3346 Poitiers, FranceMechanical Laboratory of Sousse (LMS), National Engineering School of Sousse, University of Sousse, Sousse 4000, TunisiaDepartment of GMSC, Prime Institute CNRS, ENSMA, University of Poitiers, UPR 3346 Poitiers, FranceDepartment of GMSC, Prime Institute CNRS, ENSMA, University of Poitiers, UPR 3346 Poitiers, FranceMechanical Laboratory of Sousse (LMS), National Engineering School of Sousse, University of Sousse, Sousse 4000, TunisiaMechanical Laboratory of Sousse (LMS), National Engineering School of Sousse, University of Sousse, Sousse 4000, TunisiaMechanical Laboratory of Sousse (LMS), National Engineering School of Sousse, University of Sousse, Sousse 4000, TunisiaDepartment of GMSC, Prime Institute CNRS, ENSMA, University of Poitiers, UPR 3346 Poitiers, FranceThis paper deals with the design of an optimal cable-driven parallel robot (CDPR) for upper limb rehabilitation. The robot’s prescribed workspace is identified with the help of an occupational therapist based on three selected daily life activities, which are tracked using a Qualisys motion capture system. A preliminary architecture of the robot is proposed based on the analysis of the tracked trajectories of all the activities. A multi-objective optimization process using the genetic algorithm method is then performed, where the cable tensions and the robot size are selected as the objective functions to be minimized. The cables tensions are bounded between two limits, where the lower limit ensures a positive tension in the cables at all times and the upper limit represents the maximum torque of the motor. A sensitivity analysis is then performed using the Monte Carlo method to yield the optimal design selected out of the non-dominated solutions, forming the obtained Pareto front. The robot with the highest robustness toward the disturbances is identified, and its dexterity and elastic stiffness are calculated to investigate its performance.https://www.mdpi.com/2218-6581/10/1/7cable-driven parallel robotrehabilitationdaily life activitiesmotion capturemulti-objective optimizationgenetic algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Ferdaws Ennaiem
Abdelbadiâ Chaker
Juan Sebastián Sandoval Arévalo
Med Amine Laribi
Sami Bennour
Abdelfattah Mlika
Lotfi Romdhane
Saïd Zeghloul
spellingShingle Ferdaws Ennaiem
Abdelbadiâ Chaker
Juan Sebastián Sandoval Arévalo
Med Amine Laribi
Sami Bennour
Abdelfattah Mlika
Lotfi Romdhane
Saïd Zeghloul
Sensitivity Based Selection of an Optimal Cable-Driven Parallel Robot Design for Rehabilitation Purposes
Robotics
cable-driven parallel robot
rehabilitation
daily life activities
motion capture
multi-objective optimization
genetic algorithm
author_facet Ferdaws Ennaiem
Abdelbadiâ Chaker
Juan Sebastián Sandoval Arévalo
Med Amine Laribi
Sami Bennour
Abdelfattah Mlika
Lotfi Romdhane
Saïd Zeghloul
author_sort Ferdaws Ennaiem
title Sensitivity Based Selection of an Optimal Cable-Driven Parallel Robot Design for Rehabilitation Purposes
title_short Sensitivity Based Selection of an Optimal Cable-Driven Parallel Robot Design for Rehabilitation Purposes
title_full Sensitivity Based Selection of an Optimal Cable-Driven Parallel Robot Design for Rehabilitation Purposes
title_fullStr Sensitivity Based Selection of an Optimal Cable-Driven Parallel Robot Design for Rehabilitation Purposes
title_full_unstemmed Sensitivity Based Selection of an Optimal Cable-Driven Parallel Robot Design for Rehabilitation Purposes
title_sort sensitivity based selection of an optimal cable-driven parallel robot design for rehabilitation purposes
publisher MDPI AG
series Robotics
issn 2218-6581
publishDate 2021-12-01
description This paper deals with the design of an optimal cable-driven parallel robot (CDPR) for upper limb rehabilitation. The robot’s prescribed workspace is identified with the help of an occupational therapist based on three selected daily life activities, which are tracked using a Qualisys motion capture system. A preliminary architecture of the robot is proposed based on the analysis of the tracked trajectories of all the activities. A multi-objective optimization process using the genetic algorithm method is then performed, where the cable tensions and the robot size are selected as the objective functions to be minimized. The cables tensions are bounded between two limits, where the lower limit ensures a positive tension in the cables at all times and the upper limit represents the maximum torque of the motor. A sensitivity analysis is then performed using the Monte Carlo method to yield the optimal design selected out of the non-dominated solutions, forming the obtained Pareto front. The robot with the highest robustness toward the disturbances is identified, and its dexterity and elastic stiffness are calculated to investigate its performance.
topic cable-driven parallel robot
rehabilitation
daily life activities
motion capture
multi-objective optimization
genetic algorithm
url https://www.mdpi.com/2218-6581/10/1/7
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