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Record W2757822538 · doi:10.1504/ijdsss.2017.087243

Adaptive coordinated control of multi-mobile manipulator systems

2017· article· en· W2757822538 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.

Bibliographic record

VenueInternational Journal of Digital Signals and Smart Systems · 2017
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsCanadian Space AgencyÉcole de Technologie SupérieureUniversité du Québec à Montréal
Fundersnot available
KeywordsMobile manipulatorWorkspaceControl theory (sociology)Controller (irrigation)Computer scienceObject (grammar)Stability (learning theory)Bounded functionAdaptive controlPosition (finance)Control engineeringMobile robotRobotControl (management)EngineeringArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

This paper presents an adaptive coordinated control scheme for multiple mobile manipulator robots (MMR) moving a rigid object in coordination. The dynamic parameters of the object handled and of the mobile manipulators are considered unknown but constant. The control law and the adaptation of uncertain parameters are designed using the virtual decomposition (VDC) approach. This control approach was originally applied to multiple manipulator robot systems. The proposed control design ensures that the position error in the workspace converges to zero, and that the external force error is bounded. The global stability of the system using VDC is proven through the virtual stability of each subsystem. Numerical simulations and an experimental validation are carried out for two mobile manipulators transporting an object, and are compared with the results obtained using the computed torque approach in order to show the effectiveness of the proposed controller.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score0.516

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 communication0.0000.001
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 head0.015
GPT teacher head0.237
Teacher spread0.222 · 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