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The average speed of motion and optimal power consumption in biped robots

Published online by Cambridge University Press:  19 December 2019

Vida Shams Esfanabadi
Affiliation:
Mechanical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), No. 424, Hafez Avenue, Tehran, 15875-4413, Iran e-mail: s.sadeghnejad@aut.ac.ir
Mostafa Rostami
Affiliation:
Biomedical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), No. 424, Hafez Avenue, Tehran, 15875-4413, Iran
Seyed Mohammadali Rahmati
Affiliation:
Biomedical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), No. 424, Hafez Avenue, Tehran, 15875-4413, Iran
Jacky Baltes
Affiliation:
Department of Electrical Engineering, National Taiwan Normal University, 162 Heping E Road Section 1, Taipei, 10610, Taiwan
Soroush Sadeghnejad
Affiliation:
Mechanical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), No. 424, Hafez Avenue, Tehran, 15875-4413, Iran e-mail: s.sadeghnejad@aut.ac.ir

Abstract

One of the issues that have garnered little attention, but that is nevertheless important for developing practical robots, is optimal walking conditions like power consumption during walking. The main contribution of this research is to prepare a correct walking pattern for humans who have a problem with their walking and also study the effect of average motion speed on optimal power consumption. In this study, we firstly optimize the stability and minimize the power consumption of the robot during the single support phase using parameter optimization. Our approach is based on the well-known Zero Moment Point method to calculate the stability of the proposed biped robot. Secondly, we performed experiments on healthy male, age 29 years, to analyze human walking by placing 28 markers, attached to anatomical positions and two power plates for a distance of more than one gait cycle at an average speed of 1.23 ± 0.1 m s−1 validate our results for motion analysis of correct walking ability. Our model was continuously validated by comparing the results of our empirical evaluation against the prediction of our model. The errors between experimental test and our prediction were about 4%–11% for the joint trajectories and about 0.2%–0.5% for the ground reaction forces which is acceptable for our prediction. Due to the presented model and optimized issue and predicted path, the robot can move like a person in a way that has maximum stability along with the minimum power consumption. Finally, the robot was able to walk like a specific person that we considered. This study is a case study and also can be generalized to all samples and can perform these procedures to another person’s with different features.

Type
Research Article
Copyright
© Cambridge University Press, 2019

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