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Record W2127000383 · doi:10.1177/0959651814562620

An intuitive approach for quadruped robot trotting based on virtual model control

2014· article· en· W2127000383 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

VenueProceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicRobotic Locomotion and Control
Canadian institutionsCarleton University
Fundersnot available
KeywordsSwingControl theory (sociology)RobotComputer scienceRobustness (evolution)Controller (irrigation)SimulationDiagonalControl (management)Control engineeringEngineeringArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

This article presents an intuitive approach based on virtual model control for quadrupedal dynamic locomotion, aiming at simple and robust trotting control. The controller consists of two main modules: stance phase virtual model control for full control of the robot body and swing phase virtual model control for control of swing legs. We combine the decomposed virtual model control with Raibert’s method to intuitively regulate the height, speeds and attitude of the body during stance phase, with special attention to the rotation about the body diagonal line. To unify the control law and further simplify the controller, virtual model control is also implemented for swing legs to follow the planned swing foot trajectories that are self-adapting depending on the speeds of the robot. Simulations including forward trotting, lateral push recover, and lateral travel are presented to demonstrate the effectiveness and robustness of our controller.

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: none
Teacher disagreement score0.981
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.008
GPT teacher head0.189
Teacher spread0.181 · 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