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Record W2101849315 · doi:10.1109/robot.1987.1087881

Coordinated control of multi-axis tasks

2005· article· en· W2101849315 on OpenAlexaff
G. M. Mckinnon, M. L. King, David Runnings

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsTeleoperationReflection (computer programming)TeleroboticsMaster/slaveTask (project management)Computer scienceHaptic technologyManipulator (device)Remote operationSimulationRobotControl engineeringHuman–computer interactionEngineeringArtificial intelligenceSystems engineeringMobile robotTelecommunications

Abstract

fetched live from OpenAlex

The use of manipulators and the development of manipulator technology has steadily increased in recent years. Consequently, teleoperation or the remote operation of a machine or piece of equipment has also increased. Typically, teleoperation is employed in situations where the environment is dangerous or too remote for humans to work. In space exploration with the use of dextrous manipulators, teleoperation has become a critical component. This paper describes tests carried out to evaluate three man-machine interfaces with two dextrous manipulators. The three interfaces were a master/slave system with force reflection, a master slave system without force reflection, and two six degree of freedom handcontrollers. Results indicated that task accuracy was superior with the handcontrollers. The time taken to complete the tasks with the handcontroller was longer than with the master/slave system with force reflection but with force reflection removed, no differences were found.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.011
GPT teacher head0.217
Teacher spread0.206 · 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

Citations4
Published2005
Admission routes1
Has abstractyes

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