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Record W2152993234 · doi:10.1109/iros.1993.583925

A servocompensator approach to the control of flexible space robotic manipulators with application to teleoperation

2002· article· en· W2152993234 on OpenAlexaff
M.D.M. Sever, G.M.T. D’Eleuterio

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTeleoperationControl theory (sociology)Controller (irrigation)IntegratorComputer scienceTorqueSmoothingControl engineeringRobotEngineeringArtificial intelligenceControl (management)Computer vision

Abstract

fetched live from OpenAlex

A control concept applicable to the teleoperation of multilink, structurally flexible manipulators, based on commanded velocity of the end-effector, is presented. A velocity-tracking controller is used to effect the desired motion of the manipulator. The controller seeks to minimize the velocity tracking error at the cost of allowing the links to flex. This controller is designed by precomputing gains based on a set of dynamics equations, obtained by linearizing over a space of predetermined geometrical configurations and casting them into state-space form. Appropriate real-time controller gains are determined by interpolating between a subset of those precomputed gains, corresponding to geometrical configurations, in the neighborhood of the desired configuration. The system is augmented with a second-order integrator (for torque smoothing) and further augmented by a servocompensator whose input is the error between the actual end-effector velocity and the reference (command) velocity. Although principally motivated by teleoperation, the controller can also be used in an autonomous mode, which is the focus of this paper.

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 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)0.000
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 score0.964
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

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 science0.0000.000
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 head0.014
GPT teacher head0.191
Teacher spread0.178 · 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 teacher head, 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

Citations1
Published2002
Admission routes1
Has abstractyes

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