Viability, task switching, and fall avoidance of the simplest dynamic walker

Walking humans display great versatility when achieving task goals, like avoiding obstacles or walking alongside others, but the relevance of this to fall avoidance remains unknown. We recently demonstrated a functional connection between the motor regulation needed to achieve task goals (e.g., maintaining walking speed) and a simple walker's ability to reject large disturbances. Here, for the same model, we identify the viability kernel---the largest state-space region where the walker can step forever via at least one sequence of push-off inputs per state. We further find that only a few basins of attraction of the speed-regulated walker's steady-state gaits can fully cover the viability kernel. This highlights a potentially important role of task-level motor regulation in fall avoidance. Therefore, we posit an adaptive hierarchical control/regulation strategy that switches between different task-level regulators to avoid falls. Our task switching controller only requires a target value of the regulated observable---a "task switch"---at every walking step, each chosen from a small, predetermined collection. Because humans have typically already learned to perform such goal-directed tasks during nominal walking conditions, this suggests that the "information cost" of biologically implementing such controllers for the nervous system, including cognitive demands in humans, could be quite low.

This is an Author's proofread version of the article accepted in the journal Nature Scientific Reports. The final typeset version is available online for free at https://doi.org/10.1038/s41598-022-11966-3.

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Work Title Viability, task switching, and fall avoidance of the simplest dynamic walker
Access
Open Access
Creators
  1. Navendu Patil
  2. Jonathan Dingwell
  3. Joseph Cusumano
Keyword
  1. bipedal walking
  2. task-level motor regulation
  3. viability
  4. stability
  5. fall risk
  6. basin of attraction
  7. hierarchical control
License CC BY 4.0 (Attribution)
Work Type Article
Publisher
  1. Nature Scientific Reports
Publication Date May 17, 2022
Subject
  1. Biomechanics
  2. Motor Control
  3. Dynamical Systems
  4. Robotics
  5. Neuromechanics
  6. Control Theory
Language
  1. English
Publisher Identifier (DOI)
  1. 10.1038/s41598-022-11966-3
Related URLs
Source
  1. Author's Accepted Manuscript
Deposited April 29, 2022

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Version 1
published

  • Created
  • Updated
  • Updated
  • Updated Source, Keyword, Subject, and 2 more Show Changes
    Source
    • Author's Accepted Manuscript
    Keyword
    • bipedal walking, task-level motor regulation, viability, stability, fall risk, basin of attraction, hierarchical control
    Subject
    • Biomechanics, Motor Control, Dynamical Systems, Robotics, Neuromechanics, Control Theory
    Description
    • Walking humans display great versatility when achieving task goals, like avoiding obstacles or walking alongside others, but the relevance of this to fall avoidance remains unknown. We recently demonstrated a functional connection between the motor regulation needed to achieve task goals (e.g., maintaining walking speed) and a simple walkers ability to reject large disturbances. Here, for the same model, we identify the viability kernelthe largest state-space region where the walker can
    • step forever via at least one sequence of push-off inputs per state. We further find that only a few basins of attraction of the
    • speed-regulated walkers steady-state gaits can fully cover the viability kernel. This highlights a potentially important role
    • of task-level motor regulation in fall avoidance. Therefore, we posit an adaptive hierarchical control/regulation strategy that
    • switches between different task-level regulators to avoid falls. Our task switching controller only requires a target value of the
    • regulated observable—a “task switch”—at every walking step, each chosen from a small, predetermined collection. Because
    • humans have typically already learned to perform such goal-directed tasks during nominal walking conditions, this suggests
    • that the information cost of biologically implementing such controllers for the nervous system, including cognitive demands in
    • humans, could be quite low.
    • Walking humans display great versatility when achieving task goals, like avoiding obstacles or walking alongside others, but the relevance of this to fall avoidance remains unknown. We recently demonstrated a functional connection between the motor regulation needed to achieve task goals (e.g., maintaining walking speed) and a simple walker's ability to reject large disturbances. Here, for the same model, we identify the viability kernel---the largest state-space region where the walker can step forever via at least one sequence of push-off inputs per state. We further find that only a few basins of attraction of the speed-regulated walker's steady-state gaits can fully cover the viability kernel. This highlights a potentially important role of task-level motor regulation in fall avoidance. Therefore, we posit an adaptive hierarchical control/regulation strategy that switches between different task-level regulators to avoid falls. Our task switching controller only requires a target value of the regulated observable---a "task switch"---at every walking step, each chosen from a small, predetermined collection. Because humans have typically already learned to perform such goal-directed tasks during nominal walking conditions, this suggests that the "information cost" of biologically implementing such controllers for the nervous system, including cognitive demands in humans, could be quite low.
    Related URLs
    • https://www.nature.com/srep/
  • Added Creator Navendu Patil
  • Added Creator Jonathan Dingwell
  • Added Creator Joseph Cusumano
  • Added Patil-et-al_ViabTaskSwitchFallAvoid_scirep_V4a_submit.pdf
  • Updated License Show Changes
    License
    • https://creativecommons.org/licenses/by/4.0/
  • Published
  • Updated

Version 2
published

  • Created
  • Updated
  • Published
  • Updated

Version 3
published

  • Created
  • Updated Publisher Identifier (DOI), Related URLs, Publisher's Statement Show Changes
    Publisher Identifier (DOI)
    • 10.1038/s41598-022-11966-3
    Related URLs
    • https://www.nature.com/srep/
    • https://www.biorxiv.org/content/10.1101/2022.01.16.476517v1, https://doi.org/10.5281/zenodo.6530560, https://doi.org/10.1098/rsif.2020.0278, https://doi.org/10.5281/zenodo.3871082
    Publisher's Statement
    • This is a post-peer-review, pre-copyedit version of an article published in Nature Scientific Reports. The final authenticated version will be available online for free at the Publisher's website.
    • This is an Author's version of the article accepted in the journal Nature Scientific Reports. The final typeset version is available online for free at the journal website: https://doi.org/10.1038/s41598-022-11966-3.
  • Deleted Patil-et-al_ViabTaskSwitchFallAvoid_scirep_V4a_submit.pdf
  • Added Patil-et-al_ViabTaskSwitchFallAvoid_scirep_V4b.pdf
  • Updated Publication Date Show Changes
    Publication Date
    • 2022-05
    • 2022-05-17
  • Updated Publisher's Statement Show Changes
    Publisher's Statement
    • This is an Author's version of the article accepted in the journal Nature Scientific Reports. The final typeset version is available online for free at the journal website: https://doi.org/10.1038/s41598-022-11966-3.
    • This is an Author's proofread version of the article accepted in the journal Nature Scientific Reports. The final typeset version is available online for free at https://doi.org/10.1038/s41598-022-11966-3.
  • Published
  • Updated