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Journal of biomechanics1989; 22(1); 33-41; doi: 10.1016/0021-9290(89)90182-6

Simulation of quadrupedal locomotion using a rigid body model.

Abstract: Locomotion of the horse is simulated using a mathematical model based on rigid body dynamics. A general method to generate the equations of motion for a two-dimensional rigid body model with an arbitrary number of hinge joints is presented and a numerical solution method, restricted to tree-structured models, is described. Joint movements originating from muscular forces or moments are simulated, but the method also allows that parts of the model follow strictly the pattern of kinematic data. Moment-generators with first-order linear feedback were used as a rotational muscle-equivalent. Ground-hoof interaction forces are approximated by a viscoelastic model and pseudo-Coulomb friction in vertical and horizontal directions respectively. Results of model simulations are compared to experimentally recorded data. Subsequently, adjustments are made to improve the agreement between simulation and experimental results.
Publication Date: 1989-01-01 PubMed ID: 2914970DOI: 10.1016/0021-9290(89)90182-6Google Scholar: Lookup
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  • Journal Article
  • Research Support
  • Non-U.S. Gov't

Summary

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The research article discusses how a mathematical model replicating horse locomotion based on rigid body dynamics is constructed and used to simulate movement. The findings from the simulations are then compared with actual experimentally observed data for validation and improvements.

Method for Equations of Motion Generation

In the research paper, the researchers provide a universal methodology for producing motion equations. These equations are developed for a two-dimensional rigid body model and can incorporate any number of hinge joints. This approach entails the following:

  • Construction of a mathematical model based on principles of rigid body dynamics
  • Integration of an arbitrary number of hinge joints into the model design
  • The aim is to accurately replicate the body’s complex mechanistic functions and interactions amongst various body parts.

Numerical Solution Method

The researchers then describe a numerical solution method. Its application, however, is restricted to models with a tree-like structure. Here’s what the approach involves:

  • Processing of the generated motion equations using certain computational methods
  • The computational technique is suitable only for models that resemble a tree-like structure, meaning they branch out but do not contain any loops

Simulation of Joint Movements

Simulation of joint movements originated either from muscular forces or moments is carried out in this paper. Besides, some parts of the model strictly follow the pattern of kinematic data derived from real-world observations. Here are the highlights:

  • Use of “moment-generators” with linear feedback of the first order as a representation of rotational muscle equivalents
  • Focus on maintaining realism in the model by considering actual anatomical and physiological factors like muscle-initiated joint movements

Ground-Hoof Interaction

The interaction between the ground and the horse’s hoof in the model is modeled using a viscoelastic material and a variant of Coulomb friction in the vertical and horizontal directions. The details are as follows:

  • Application of a viscoelastic model and a pseudo-Coulomb friction model to imitate the interaction between the horse’s hoof and the ground, which is crucial in locomotion
  • Semblance of a viscoelastic model, representing the hoof’s ability to slightly deform when coming into contact with the ground and subsequently regain its shape
  • Use of pseudo-Coulomb friction to portray the resistance to motion due to frictional forces between the hoof and the surface

Comparisons with Experimental Data

The results obtained from model simulations are compared to data recorded from actual experiments. This allows the researchers to validate their model and carry out modifications for enhancement. The comparisons entailed:

  • Comparing the simulation results against real-world data to evaluate their accuracy and reliability
  • Based on these comparisons, any discrepancies identified are corrected by revising and refining the model accordingly

Cite This Article

APA
van den Bogert AJ, Schamhardt HC, Crowe A. (1989). Simulation of quadrupedal locomotion using a rigid body model. J Biomech, 22(1), 33-41. https://doi.org/10.1016/0021-9290(89)90182-6

Publication

ISSN: 0021-9290
NlmUniqueID: 0157375
Country: United States
Language: English
Volume: 22
Issue: 1
Pages: 33-41

Researcher Affiliations

van den Bogert, A J
  • Department of Veterinary Anatomy, Utrecht University, The Netherlands.
Schamhardt, H C
    Crowe, A

      MeSH Terms

      • Animals
      • Biomechanical Phenomena
      • Computer Simulation
      • Horses / physiology
      • Locomotion
      • Models, Biological
      • Movement
      • Software

      Citations

      This article has been cited 10 times.
      1. Pagliara E, Pasinato A, Valazza A, Riccio B, Cantatore F, Terzini M, Putame G, Parrilli A, Sartori M, Fini M, Zanetti EM, Bertuglia A. Multibody Computer Model of the Entire Equine Forelimb Simulates Forces Causing Catastrophic Fractures of the Carpus during a Traditional Race.. Animals (Basel) 2022 Mar 16;12(6).
        doi: 10.3390/ani12060737pubmed: 35327134google scholar: lookup
      2. Jones OY, Raschke SU, Riches PE. Inertial properties of the German Shepherd Dog.. PLoS One 2018;13(10):e0206037.
        doi: 10.1371/journal.pone.0206037pubmed: 30339688google scholar: lookup
      3. Sellers WI, Hirasaki E. Quadrupedal locomotor simulation: producing more realistic gaits using dual-objective optimization.. R Soc Open Sci 2018 Mar;5(3):171836.
        doi: 10.1098/rsos.171836pubmed: 29657790google scholar: lookup
      4. Fu C, Suzuki Y, Kiyono K, Morasso P, Nomura T. An intermittent control model of flexible human gait using a stable manifold of saddle-type unstable limit cycle dynamics.. J R Soc Interface 2014 Dec 6;11(101):20140958.
        doi: 10.1098/rsif.2014.0958pubmed: 25339687google scholar: lookup
      5. Ackermann M, van den Bogert AJ. Predictive simulation of gait at low gravity reveals skipping as the preferred locomotion strategy.. J Biomech 2012 Apr 30;45(7):1293-8.
      6. Ackermann M, van den Bogert AJ. Optimality principles for model-based prediction of human gait.. J Biomech 2010 Apr 19;43(6):1055-60.
      7. Payne RC, Crompton RH, Isler K, Savage R, Vereecke EE, Günther MM, Thorpe SK, D'Août K. Morphological analysis of the hindlimb in apes and humans. II. Moment arms.. J Anat 2006 Jun;208(6):725-42.
      8. Payne RC, Crompton RH, Isler K, Savage R, Vereecke EE, Günther MM, Thorpe SK, D'Août K. Morphological analysis of the hindlimb in apes and humans. I. Muscle architecture.. J Anat 2006 Jun;208(6):709-24.
      9. Payne RC, Veenman P, Wilson AM. The role of the extrinsic thoracic limb muscles in equine locomotion.. J Anat 2005 Feb;206(2):193-204.
      10. Payne RC, Veenman P, Wilson AM. The role of the extrinsic thoracic limb muscles in equine locomotion.. J Anat 2004 Dec;205(6):479-90.