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Record W2109470906 · doi:10.1109/3477.979968

Robust damping control of mobile manipulators

2002· article· en· W2109470906 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

VenueIEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · 2002
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsControl theory (sociology)Mobile manipulatorKinematicsController (irrigation)Robust controlControl engineeringBounded functionComputer scienceMotion controlStability (learning theory)Mobile robotManipulator (device)Control (management)Control systemEngineeringRobotMathematicsArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

A novel robust control technique, robust damping control (RDC), is introduced. An RDC controller is further developed for the motion control of a mobile manipulator subject to kinematic constraints. The knowledge of dynamic parameters of the mobile manipulator is assumed to be completely unknown. The proposed RDC controller is capable of disturbance-rejection in the presence of unknown bounded disturbance, without requiring the knowledge of its bound. The stability of the closed-loop system is guaranteed. The controller has a simple structure and can be easily implemented in applications. Experimental tests on a 2-DOF robotic manipulator illustrate that the proposed control is significantly better than conventional robust control.

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 categoriesMeta-epidemiology (narrow)
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 score0.684
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.018
GPT teacher head0.190
Teacher spread0.172 · 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