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Record W2130408725 · doi:10.1109/acc.2005.1470345

Force/position output feedback tracking control of holonomically constrained rigid bodies

2005· article· en· W2130408725 on OpenAlexaff
K. Melhem, E.K. Boukas, Luc Baron

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsControl theory (sociology)Rigid bodyPosition (finance)Contact forceTracking (education)Mechanical systemController (irrigation)Robot end effectorComputer scienceBody forceControl engineeringControl (management)EngineeringPhysicsClassical mechanicsRobotArtificial intelligence

Abstract

fetched live from OpenAlex

In this note a new concept of force/position control approach for holonomically constrained rigid body systems is introduced. With this force control approach, the forces of the mechanical constraints between the rigid bodies as well as the forces of the constraints when the system's end effector interacting with the environment are to be directly controlled to desired trajectories. Our force control strategy is based on the use of a new dynamic model for constrained rigid body systems that determines the equations of the mechanical constraints between the elements of the constrained rigid body system in closed form. Our controller for the rigid body system during constrained motion ensures exponential position, end effector contact force and mechanical force tracking, and requires only position measurements.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 science0.0010.001
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 head0.006
GPT teacher head0.193
Teacher spread0.187 · 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 designNot applicable
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

Citations2
Published2005
Admission routes1
Has abstractyes

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