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Record W2012627590 · doi:10.1115/1.1898228

Design of Joint Angle Profiles for a Planar Five-Link Bipedal System

2004· article· en· W2012627590 on OpenAlexafffund
Q. Wu, Chung Ying Chan

Bibliographic record

VenueJournal of Dynamic Systems Measurement and Control · 2004
Typearticle
Languageen
FieldEngineering
TopicRobotic Locomotion and Control
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsKinematicsGaitSwingWork (physics)Joint (building)BipedalismEffect of gait parameters on energetic costKnee JointGround reaction forceMechanical energyComputer scienceTrunkBiomechanicsPlanarSimulationControl theory (sociology)Feature (linguistics)Energy (signal processing)Gait analysisMathematicsPhysical medicine and rehabilitationEngineeringPhysicsArtificial intelligenceStructural engineeringMechanical engineeringGeologyClassical mechanics

Abstract

fetched live from OpenAlex

A set of joint angle profiles for a five-link bipedal model walking on level ground is designed. One feature of the joint angle profiles is that after an impulsive energy injection at an early stage of each step, the mechanical energy of the bipedal system remains constant for the rest of the step. This feature is of special interest in the studies of energetics of bipedal walking and can be beneficial to the design of modern energy-storing prosthetic feet. The joint angle profiles also satisfy four kinematic constraints, i.e., the walking speed, stance knee bias, upright posture of the trunk and motion coordination. To obtain acceptable gait patterns, a set of parameters is carefully tuned to satisfy extra conditions (repeatable gait, no hyperextension, and no scuffing at the swing knee). This work can provide some insight into the mechanics of bipedal walking and has potential to establish a framework for estimating the optimal energy storage of modern prosthetic feet.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.197
Teacher spread0.174 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2004
Admission routes2
Has abstractyes

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