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Record W2269562201 · doi:10.3390/machines4010005

Joint Mechanism That Mimics Elastic Characteristics in Human Running

2016· article· en· W2269562201 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

VenueMachines · 2016
Typearticle
Languageen
FieldEngineering
TopicRobotic Locomotion and Control
Canadian institutionsUniversity of Calgary
FundersMinistry of Education, Culture, Sports, Science and Technology
KeywordsTorsion springJoint stiffnessStiffnessLeaf springSpring (device)Joint (building)Mechanism (biology)Knee JointTorsion (gastropod)Structural engineeringElasticity (physics)Computer scienceMaterials scienceControl theory (sociology)EngineeringPhysicsAnatomyComposite materialArtificial intelligence

Abstract

fetched live from OpenAlex

Analysis of human running has revealed that the motion of the human leg can be modeled by a compression spring because the joints of the leg behave like a torsion spring in the stance phase. In this paper, we describe the development of a joint mechanism that mimics the elastic characteristics of the joints of the stance leg. The knee was equipped with a mechanism comprising two laminated leaf springs made of carbon fiber-reinforced plastic for adjusting the joint stiffness and a worm gear in order to achieve active movement. Using this mechanism, we were able to achieve joint stiffness mimicking that of a human knee joint that can be adjusted by varying the effective length of one of the laminated leaf springs. The equation proposed for calculating the joint stiffness considers the difference between the position of the fixed point of the leaf spring and the position of the rotational center of the joint. We evaluated the performance of the laminated leaf spring and the effectiveness of the proposed equation for joint stiffness. We were able to make a bipedal robot run with one leg using pelvic oscillation for storing energy produced by the resonance related to leg elasticity.

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 score0.725
Threshold uncertainty score0.346

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 head0.014
GPT teacher head0.206
Teacher spread0.192 · 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