Predicting the metabolic energy costs of bipedalism using evolutionary robotics
To understand the evolution of bipedalism among the homnoids in an ecological context we need to be able to estimate theenerrgetic cost of locomotion in fossil forms. Ideally such an estimate would be based entirely on morphology since, except for the rare instances where footprints are preserved,...
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| Format: | Article |
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The Company of Biologists Ltd.
2003
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| Online Access: | https://eprints.nottingham.ac.uk/376/ |
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| author | Sellers, William Irvin Dennis, Louise Abigail Crompton, Robin Hugh |
| author_facet | Sellers, William Irvin Dennis, Louise Abigail Crompton, Robin Hugh |
| author_sort | Sellers, William Irvin |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | To understand the evolution of bipedalism among the homnoids in an ecological context we need to be able to estimate theenerrgetic cost of locomotion in fossil forms. Ideally such an estimate would be based entirely on morphology since, except for the rare instances where footprints are preserved, this is hte only primary source of evidence available. In this paper we use evolutionary robotics techniques (genetic algoritms, pattern generators and mechanical modeling) to produce a biomimentic simulation of bipedalism based on human body dimensions. The mechnaical simulation is a seven-segment, two-dimensional model with motive force provided by tension generators representing the major muscle groups acting around the lower-limb joints. Metabolic energy costs are calculated from the muscel model, and bipedal gait is generated using a finite-state pattern generator whose parameters are produced using a genetic algorithm with locomotor economy (maximum distance for a fixed energy cost) as the fitness criterion. The model is validated by comparing the values it generates with those for modern humans. The result (maximum efficiency of 200 J m-1) is within 15% of the experimentally derived value, which is very encouraging and suggests that this is a useful analytic technique for investigating the locomotor behaviour of fossil forms. Initial work suggests that in the future this technique could be used to estimate other locomotor parameters such as top speed. In addition, the animations produced by this technique are qualitatively very convincing, which suggests that this may also be a useful technique for visualizing bipedal locomotion. |
| first_indexed | 2025-11-14T18:12:04Z |
| format | Article |
| id | nottingham-376 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:12:04Z |
| publishDate | 2003 |
| publisher | The Company of Biologists Ltd. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-3762020-05-04T20:32:07Z https://eprints.nottingham.ac.uk/376/ Predicting the metabolic energy costs of bipedalism using evolutionary robotics Sellers, William Irvin Dennis, Louise Abigail Crompton, Robin Hugh To understand the evolution of bipedalism among the homnoids in an ecological context we need to be able to estimate theenerrgetic cost of locomotion in fossil forms. Ideally such an estimate would be based entirely on morphology since, except for the rare instances where footprints are preserved, this is hte only primary source of evidence available. In this paper we use evolutionary robotics techniques (genetic algoritms, pattern generators and mechanical modeling) to produce a biomimentic simulation of bipedalism based on human body dimensions. The mechnaical simulation is a seven-segment, two-dimensional model with motive force provided by tension generators representing the major muscle groups acting around the lower-limb joints. Metabolic energy costs are calculated from the muscel model, and bipedal gait is generated using a finite-state pattern generator whose parameters are produced using a genetic algorithm with locomotor economy (maximum distance for a fixed energy cost) as the fitness criterion. The model is validated by comparing the values it generates with those for modern humans. The result (maximum efficiency of 200 J m-1) is within 15% of the experimentally derived value, which is very encouraging and suggests that this is a useful analytic technique for investigating the locomotor behaviour of fossil forms. Initial work suggests that in the future this technique could be used to estimate other locomotor parameters such as top speed. In addition, the animations produced by this technique are qualitatively very convincing, which suggests that this may also be a useful technique for visualizing bipedal locomotion. The Company of Biologists Ltd. 2003 Article PeerReviewed Sellers, William Irvin, Dennis, Louise Abigail and Crompton, Robin Hugh (2003) Predicting the metabolic energy costs of bipedalism using evolutionary robotics. The Journal of Experimental Biology, 206 . pp. 1127-1136. bipdelism biomechanics locomotion evolutionary robotics human |
| spellingShingle | bipdelism biomechanics locomotion evolutionary robotics human Sellers, William Irvin Dennis, Louise Abigail Crompton, Robin Hugh Predicting the metabolic energy costs of bipedalism using evolutionary robotics |
| title | Predicting the metabolic energy costs of bipedalism using evolutionary robotics |
| title_full | Predicting the metabolic energy costs of bipedalism using evolutionary robotics |
| title_fullStr | Predicting the metabolic energy costs of bipedalism using evolutionary robotics |
| title_full_unstemmed | Predicting the metabolic energy costs of bipedalism using evolutionary robotics |
| title_short | Predicting the metabolic energy costs of bipedalism using evolutionary robotics |
| title_sort | predicting the metabolic energy costs of bipedalism using evolutionary robotics |
| topic | bipdelism biomechanics locomotion evolutionary robotics human |
| url | https://eprints.nottingham.ac.uk/376/ |