Literature DB >> 21079285

Robust and efficient walking with spring-like legs.

J Rummel1, Y Blum, A Seyfarth.   

Abstract

The development of bipedal walking robots is inspired by human walking. A way of implementing walking could be performed by mimicking human leg dynamics. A fundamental model, representing human leg dynamics during walking and running, is the bipedal spring-mass model which is the basis for this paper. The aim of this study is the identification of leg parameters leading to a compromise between robustness and energy efficiency in walking. It is found that, compared to asymmetric walking, symmetric walking with flatter angles of attack reveals such a compromise. With increasing leg stiffness, energy efficiency increases continuously. However, robustness is the maximum at moderate leg stiffness and decreases slightly with increasing stiffness. Hence, an adjustable leg compliance would be preferred, which is adaptable to the environment. If the ground is even, a high leg stiffness leads to energy efficient walking. However, if external perturbations are expected, e.g. when the robot walks on uneven terrain, the leg should be softer and the angle of attack flatter. In the case of underactuated robots with constant physical springs, the leg stiffness should be larger than k = 14 in order to use the most robust gait. Soft legs, however, lack in both robustness and efficiency.

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Year:  2010        PMID: 21079285     DOI: 10.1088/1748-3182/5/4/046004

Source DB:  PubMed          Journal:  Bioinspir Biomim        ISSN: 1748-3182            Impact factor:   2.956


  3 in total

1.  Walking in circles: a modelling approach.

Authors:  Horst-Moritz Maus; Andre Seyfarth
Journal:  J R Soc Interface       Date:  2014-10-06       Impact factor: 4.118

2.  Predicting ground reaction forces of human gait using a simple bipedal spring-mass model.

Authors:  Michael Mauersberger; Falk Hähnel; Klaus Wolf; Johannes F C Markmiller; Alexander Knorr; Dominik Krumm; Stephan Odenwald
Journal:  R Soc Open Sci       Date:  2022-07-27       Impact factor: 3.653

3.  Comparing system identification techniques for identifying human-like walking controllers.

Authors:  Dave Schmitthenner; Anne E Martin
Journal:  R Soc Open Sci       Date:  2021-12-22       Impact factor: 2.963

  3 in total

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