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Record W2544242607 · doi:10.1109/ichr.2004.1442689

Stability control of a 6 DOF biped in the dual-support phase using fuzzy control

2005· article· en· W2544242607 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotic Locomotion and Control
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsControl theory (sociology)TorqueFuzzy control systemController (irrigation)Fuzzy logicRobotLift (data mining)Center of gravityComputer scienceAnkleAngular velocityPosition (finance)Dual (grammatical number)Control (management)Artificial intelligencePhysics

Abstract

fetched live from OpenAlex

This work investigates the feasibility of using a fuzzy controller to stabilize a biped robot in the dual-support phase. Taking as inputs the errors of the angular position and angular velocity for each joint, the controller uses a rule-base implemented with five membership functions to compute the joint torques of a 6 DOF biped robot. The input gains were computed at run-time using the Hip and Ankle Strategy (HAS), which sets a gain value for each joint based on the relative position of the center of gravity with respect to the support area. Although the Hip and Ankle Strategy was found to increase the computational load without enhancing the actuation response, the results have clearly showed the success of the fuzzy control scheme in making the non-linear system stable, as well as in placing the robot into the most stable posture without having to lift the feet of the ground.

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)0.001
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 score0.408
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.020
GPT teacher head0.257
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

Quick stats

Citations3
Published2005
Admission routes1
Has abstractyes

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