Literature DB >> 31146191

Locomotor pattern and mechanical exchanges during collective load transport.

Guillaume Fumery1, Hugo Mérienne2, Vincent Fourcassié2, Pierre Moretto3.   

Abstract

While the locomotor behavior of humans walking alone, loaded or unloaded, has been extensively studied, the locomotor behavior of humans transporting a load collectively is very poorly documented in the biomechanics literature. Yet, collective carriage is a task commonly performed in sport (CrossFit), military and health care (carriage of an injured person) activities and is a task that raises growing interest in robotics (Cobots). The primary aim of our research was to test the hypothesis that the mechanical cost of locomotion is comparable when two individuals are transporting an object collectively and when they are walking alone. To test this, the movements of ten pairs of individuals walking side by side, separately or while transporting collectively an object, were recorded with a three-dimensional motion analysis system (Vicon©). Our results show a similar pattern in the periodic displacement of the center of mass and in mechanical costs, between individuals walking alone and individuals carrying a load collectively. Moreover, a better pendulum-like behavior was found in the sagittal plane and in 3D for the pairs of individuals carrying an object, which suggests that the saving in mechanical exchanges is higher when two individuals are carrying an object collectively than when they are walking alone. The values of the parameters measured in our experiment could be used as a benchmark for the implementation of collective carriage tasks in robotics.
Copyright © 2019. Published by Elsevier B.V.

Entities:  

Keywords:  Center of mass; Collective behavior; Gait; Locomotion; Transport

Year:  2019        PMID: 31146191     DOI: 10.1016/j.humov.2019.05.012

Source DB:  PubMed          Journal:  Hum Mov Sci        ISSN: 0167-9457            Impact factor:   2.161


  2 in total

1.  Walking paths during collaborative carriages do not follow the simple rules observed in the locomotion of single walking subjects.

Authors:  Isabelle Maroger; Manon Silva; Hélène Pillet; Nicolas Turpin; Olivier Stasse; Bruno Watier
Journal:  Sci Rep       Date:  2022-09-16       Impact factor: 4.996

2.  Analysis of Human Exercise Health Monitoring Data of Smart Bracelet Based on Machine Learning.

Authors:  Xiaoge Ma
Journal:  Comput Intell Neurosci       Date:  2022-06-08
  2 in total

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