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Record W2169648650 · doi:10.1109/ccece.1999.804902

Adaptive force/position control of a robot hand

2003· article· en· W2169648650 on OpenAlexaff
Martin De Montigny, Pierre Sicard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsControl theory (sociology)Controller (irrigation)TrajectoryKinematicsPosition (finance)Impedance controlAdaptive controlComputer scienceControl engineeringRobotNonlinear systemAutomationRobot kinematicsObject (grammar)Motion controlContact forceEngineeringArtificial intelligenceMobile robotControl (management)

Abstract

fetched live from OpenAlex

Presents a position/force control algorithm for a robot hand grasping a flexible object. The adaptive control algorithm of Slotine and Li (1991) is employed for realising an adaptive position controller for the variation of masses of the fingers during unconstrained movement. A PI nonlinear force controller modifies the position trajectory until the contacts reach the objects to be grasped. The controller parameters are adjusted for minimising the rebounding produced by contact between the hand and its environment. A task planner permits the automation of the motion of the controllers and the processes of grasping the object. The simulation results of a three fingered hand demonstrates the stability and effectiveness of the controllers in the presence of surface impedance variation and kinematic error modelling.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.202
Teacher spread0.188 · 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 designBench or experimental
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
Published2003
Admission routes1
Has abstractyes

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