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Record W2554744805 · doi:10.1115/1.4035234

Tip-Over Stability Analysis for a Wheeled Mobile Manipulator

2016· article· en· W2554744805 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

VenueJournal of Dynamic Systems Measurement and Control · 2016
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsToronto Metropolitan University
FundersBeijing Municipal Science and Technology CommissionScience and Technology Commission of Shanghai Municipality
KeywordsControl theory (sociology)Payload (computing)Manipulator (device)Position (finance)Mobile manipulatorCenter of gravityInertial frame of referenceStability (learning theory)Motion planningComputer sciencePath (computing)Motion (physics)SimulationMobile robotRobotPhysicsClassical mechanicsArtificial intelligence

Abstract

fetched live from OpenAlex

A method is presented for tip-over stability analysis of a wheeled mobile manipulator. A wheeled mobile manipulator may tip over resulting from its operation. In this study, first a Newton–Euler formulation is applied to formulate the manipulator’s reaction forces and moments exerted onto the mobile platform. Tip-over criterion is derived to judge the system stability. Three load and motion analyses are carried on. The first static load deals with links and payload to show the effect of the horizontal position of the system’s center of gravity (CG). The second and third are the inertial forces resulting from joint speeds and accelerations, respectively. Case study is path planning with tip-over criterion result which can make the system stable along the path. The simulation results demonstrate the effectiveness of the proposed method.

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)0.002
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 score0.823
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.013
GPT teacher head0.201
Teacher spread0.188 · 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