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Computer optimization of a minimal biped model discovers walking and running

Author

Listed:
  • Manoj Srinivasan

    (Theoretical and Applied Mechanics, Cornell University)

  • Andy Ruina

    (Theoretical and Applied Mechanics, Cornell University)

Abstract

Walk don't pendulate From the infinite number of gaits that human legs are capable of, we choose either to walk or run. Is this because these are the most energetically efficient gaits available? Srinivasan and Ruina used a computational model to evaluate an infinity of different gaits by reducing them to principles of simple newtonian mechanics, calculating how much energy each style requires to move the same mass. They find that walking, running and a mixture of the two called ‘pendular running’ each have speeds where they are the optimal gaits. Real people, however, eschew pendular running entirely, so the simple picture of locomotion provided by the model may overlook factors that make pendular running impractical in the real world.

Suggested Citation

  • Manoj Srinivasan & Andy Ruina, 2006. "Computer optimization of a minimal biped model discovers walking and running," Nature, Nature, vol. 439(7072), pages 72-75, January.
    • Handle: RePEc:nat:nature:v:439:y:2006:i:7072:d:10.1038_nature04113
    DOI: 10.1038/nature04113
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    Cited by:

    1. Ahalya Prabhakar & Todd Murphey, 2022. "Mechanical intelligence for learning embodied sensor-object relationships," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    2. Nidhi Seethapathi & Barrett C. Clark & Manoj Srinivasan, 2024. "Exploration-based learning of a stabilizing controller predicts locomotor adaptation," Nature Communications, Nature, vol. 15(1), pages 1-23, December.
    3. Jonathan B Dingwell & Joseph P Cusumano, 2019. "Humans use multi-objective control to regulate lateral foot placement when walking," PLOS Computational Biology, Public Library of Science, vol. 15(3), pages 1-28, March.
    4. Jonathan B Dingwell & Joby John & Joseph P Cusumano, 2010. "Do Humans Optimally Exploit Redundancy to Control Step Variability in Walking?," PLOS Computational Biology, Public Library of Science, vol. 6(7), pages 1-15, July.
    5. J Lucas McKay & Lena H Ting, 2012. "Optimization of Muscle Activity for Task-Level Goals Predicts Complex Changes in Limb Forces across Biomechanical Contexts," PLOS Computational Biology, Public Library of Science, vol. 8(4), pages 1-17, April.
    6. Siddhartha Bikram Panday & Prabhat Pathak & Jeheon Moon & Dohoon Koo, 2022. "Complexity of Running and Its Relationship with Joint Kinematics during a Prolonged Run," IJERPH, MDPI, vol. 19(15), pages 1-24, August.

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