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Record W4387354638 · doi:10.1145/3623264.3624448

Physical Simulation of Balance Recovery after a Push

2023· preprint· en· W4387354638 on OpenAlexaff
Alexis Jensen, Thomas Chatagnon, Niloofar Khoshsiyar, Daniele Reda, Michiel van de Panne, Charles Pontonnier, Julien Pettré

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicHuman Motion and Animation
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaUniversity of British Columbia Hospital
FundersH2020 Future and Emerging TechnologiesAgence Nationale de la RechercheEuropean Commission
KeywordsBalance (ability)Computer sciencePhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

Our goal is to simulate how humans recover balance after external perturbation, e.g., being pushed. While different strategies can be adopted to achieve balance recovery, we particularly aim at replicating how humans combine the control of their support area with the control of their body movement to regain balance when it is necessary. We develop a physics-based approach to simulate balance recovery, with two main contributions to achieve our goal: a foot control technique to adjust the shape of a character’s support zone to the motion of its center of mass (CoM), and the dynamic control of the CoM to maintain its vertical projection in this same zone. We also calibrate the simulation by optimisation, before validating our results against experimental data.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.259
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

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