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Record W2106321774 · doi:10.1109/oceans.2008.5151915

Development of a coordinated controller for underwater vehicle-manipulator systems

2008· article· en· W2106321774 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsControl theory (sociology)Remotely operated underwater vehicleRedundancy (engineering)Computer scienceControl engineeringController (irrigation)Lyapunov functionUnmanned underwater vehicleUnderwaterEngineeringMobile robotRobotArtificial intelligenceNonlinear systemControl (management)

Abstract

fetched live from OpenAlex

In this work, the motions of an underwater remotely operated vehicle (ROV) and a spatial manipulator are coordinated using a consolidated controller. The controller translates a single pilot command, the desired position and orientation of the end effector, into a coordinated set of ROV and manipulator joint motions that satisfy the pilot intent in addition to a series of secondary objectives. The controller relies on a unified dynamic model of the system. The quasi-Lagrange method is used to derive the equations of motion in terms of the ROV body-fixed frame. For the control problem, a novel sliding-mode based controller is proposed. The controller contains two layers of adaptivity. The first layer is for adjusting PID gains, whereas the second layer is for estimating the bound on a lumped uncertainty vector. The second level of adaptation is shown to relax the Lyapunov stability requirements leading to a more robust controller. To generate reference state values, a redundancy resolution technique is utilized that is based on the gradient projection method merged with a fuzzy determination of the hierarchy of the secondary objectives. The redundancy resolution method distributes the pilot's end-effector command over the ROV and the manipulator in an optimal manner using the redundant degrees of freedom. The results illustrate that detailed subsea tasks can be completed with a small, low-cost ROVM system using the proposed unified control scheme.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.722
Threshold uncertainty score0.538

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 head0.041
GPT teacher head0.226
Teacher spread0.185 · 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

Quick stats

Citations9
Published2008
Admission routes2
Has abstractyes

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