scholarly journals Quantifying the human-robot interaction forces between a lower limb exoskeleton and healthy users

Author(s):  
Ashish Rathore ◽  
Matthew Wilcox ◽  
Dafne Zuleima Morgado Ramirez ◽  
Rui Loureiro ◽  
Tom Carlson
2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Zhenlei Chen ◽  
Qing Guo ◽  
Huiyu Xiong ◽  
Dan Jiang ◽  
Yao Yan

AbstractIn this study, a humanoid prototype of 2-DOF (degrees of freedom) lower limb exoskeleton is introduced to evaluate the wearable comfortable effect between person and exoskeleton. To improve the detection accuracy of the human-robot interaction torque, a BPNN (backpropagation neural networks) is proposed to estimate this interaction force and to compensate for the measurement error of the 3D-force/torque sensor. Meanwhile, the backstepping controller is designed to realize the exoskeleton's passive position control, which means that the person passively adapts to the exoskeleton. On the other hand, a variable admittance controller is used to implement the exoskeleton's active follow-up control, which means that the person's motion is motivated by his/her intention and the exoskeleton control tries best to improve the human-robot wearable comfortable performance. To improve the wearable comfortable effect, serval regular gait tasks with different admittance parameters and step frequencies are statistically performed to obtain the optimal admittance control parameters. Finally, the BPNN compensation algorithm and two controllers are verified by the experimental exoskeleton prototype with human-robot cooperative motion.


Author(s):  
Mahdi Haghshenas-Jaryani ◽  
Muthu B. J. Wijesundara

This paper presents the development of a framework based on a quasi-statics concept for modeling and analyzing the physical human-robot interaction in soft robotic hand exoskeletons used for rehabilitation and human performance augmentation. This framework provides both forward and inverse quasi-static formulations for the interaction between a soft robotic digit and a human finger which can be used for the calculation of angular motions, interaction forces, actuation torques, and stiffness at human joints. This is achieved by decoupling the dynamics of the soft robotic digit and the human finger with similar interaction forces acting on both sides. The presented theoretical models were validated by a series of numerical simulations based on a finite element model which replicates similar human-robot interaction. The comparison of the results obtained for the angular motion, interaction forces, and the estimated stiffness at the joints indicates the accuracy and effectiveness of the quasi-static models for predicting the human-robot interaction.


2021 ◽  
pp. 683-690
Author(s):  
Irene Pippo ◽  
Jacopo Zenzeri ◽  
Giovanni Berselli ◽  
Diego Torazza

2019 ◽  
Vol 112 ◽  
pp. 323-331 ◽  
Author(s):  
Arnaldo G. Leal-Junior ◽  
Camilo R. Díaz ◽  
Maria José Pontes ◽  
Carlos Marques ◽  
Anselmo Frizera

2016 ◽  
Vol 3 (4) ◽  
pp. 273-279 ◽  
Author(s):  
Matthew Wilcox ◽  
Ashish Rathore ◽  
Dafne Zuleima Morgado Ramirez ◽  
Rui C.V. Loureiro ◽  
Tom Carlson

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