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Record W2102243952 · doi:10.1109/cca.2005.1507276

Effects of gravity and friction constraints on bipedal balance control

2005· article· en· W2102243952 on OpenAlexaff
Congling Yang, Q. Wu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotic Locomotion and Control
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsConstraint (computer-aided design)TorqueControl theory (sociology)Angular velocityPosition (finance)Work (physics)Balance (ability)Control (management)MathematicsPhysicsComputer scienceClassical mechanicsGeometryEconomics

Abstract

fetched live from OpenAlex

The satisfaction of constraints between the foot and the ground during balancing of bipedal standing is important. In this work, the effects of two constraints, namely the gravity constraint and the friction constraint, on balancing of a simplified two-dimensional biped are considered. The bounds imposed on the control torque are first determined analytically. Such results not only show the specific constraint causing the control bounds, but also indicate the possible violation of the individual constraint. It is also found that the angular velocity plays a crucial role in satisfying the constraints. More importantly, it is found that in a region around the upright position within the critical angles, if the angular velocity is above the critical one, regardless of the control torque, the constraints cannot be satisfied. Another interesting finding is that between the gravity constraint and the friction constraint, the friction constraint is more dominant, thus should be considered carefully

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)0.002
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.002
GPT teacher head0.179
Teacher spread0.176 · 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

Citations9
Published2005
Admission routes1
Has abstractyes

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