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Record W2048751110 · doi:10.1142/s0219843610002052

EFFECTS OF RAMP ANGLE AND MASS DISTRIBUTIONS ON PASSIVE DYNAMIC GAIT — AN EXPERIMENTAL STUDY

2010· article· en· W2048751110 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Humanoid Robotics · 2010
Typearticle
Languageen
FieldEngineering
TopicRobotic Locomotion and Control
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsRobustness (evolution)GaitWork (physics)Computer scienceCenter of mass (relativistic)SimulationPreferred walking speedMass distributionControl theory (sociology)MechanicsPhysicsPhysical medicine and rehabilitationArtificial intelligenceControl (management)

Abstract

fetched live from OpenAlex

A bipedal walking mechanism with knees is designed and built to study the passive dynamic gait. The effects of changing the ramp angle and the mass distributions of the thighs and the shanks on the gait patterns and walking robustness are studied. It is shown that the changes in the ramp angle and the mass distribution have significant effects on the step lengths and the robustness (the successful rate of launching and the step-count) of the passive gait. More specifically, as the ramp angle increases or the mass center of the entire walker is raised, the step length increases, which dictates the walking speed. However, our experiments show that the changes in the ramp angle and the mass distribution have slight effects on the step period. The optimal ramp angle and mass distribution of the passive walker are also identified, of which the passive walker has the highest successful rate of launching and the step-count. Our experimental results are compared with previous work based on simulations. This research can provide important information for validating/adjusting mathematical models of passive dynamic walking. The work also enables us to gain a better understanding of the mechanics of walking.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.412

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 head0.005
GPT teacher head0.252
Teacher spread0.248 · 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