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Record W2950981022 · doi:10.82308/18545

The design of innovative epicyclic mechanical transmissions : application to the drives of wheeled mobile robots

2006· article· en· W2950981022 on OpenAlexfundno aff
Chao Chen

Bibliographic record

VenueeScholarship@McGill (McGill) · 2006
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsGear trainBacklashTransmission (telecommunications)Power (physics)Mechanism (biology)Pressure angleStiffnessPower transmissionGear ratioEngineeringRoboticsComputer scienceMechanical engineeringControl theory (sociology)SimulationRobotArtificial intelligenceStructural engineeringElectrical engineeringPhysicsControl (management)

Abstract

fetched live from OpenAlex

Epicyclic mechanisms have found wide applications in industry, especially in automobiles and robotics. Low efficiency due to the high gearing power occurring in an epicyclic train is an important problem. This thesis develops a novel family of epicyclic transmissions, based on cams and rollers. This kind of cam-based mechanical transmissions, Speed-o-Cam (SoC), offers features such as high stiffness, low backlash, and high efficiency. We develop multi-lobbed cam profiles, the sun cam and the ring cam, which comprise an epicyclic cam train (ECT) with the roller follower. New design criteria are established: the generalized transmission index (GTI) and the contact ratio in cam transmissions. The GTI is an index that quantifies the force transmission quality in a mechanism, thereby generalizing the pressure angle, the transmission angle, and the transmission index (TI) proposed by Sutherland and Roth in 1973. The contact ratio is an index of the quantity of overlap occurring between two conjugate cams during transmission. A contact ratio greater than unity guarantees smooth motion during operation. In order to avoid "poor" transmission, we apply an undercutting technique on the cam profile to achieve a smooth motion. We introduce two new concepts, virtual power and virtual power ratio, and derive an original algorithm to compute the efficiency in an epicyclic train upon the assumption that power loss is due only to friction upon meshing. The results show that friction has a larger effect on the total efficiency of an epicyclic train than on a simple train. Examples are given to validate this algorithm, by comparison of our results with previous works. The dual-wheel transmission (DWT), proposed elsewhere using epicyclic gear trains (EGTs), is designed here with epicyclic trains of cams and rollers. We optimize the DWT to achieve a compact design and a high transmission performance. Furthermore, we define the total transmission index (TTI), which allow us to evaluate the final DWT design. Two virtual prototypes of the DWT, the central and the offset versions, are generated: the former is capable of quasi-omnidirectional mobility, the latter of full omnidirectional mobility. Finally, we include a general kinematic analysis of wheeled mobile robots (WMRs) with single-wheel drives and apply this method to WMRs with DWT units; then, we obtain symbolic solutions to the direct kinematics (DK) and inverse kinematics (IK) problems, for both central and offset types of units.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.240
Teacher spread0.226 · 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 designBench or experimental
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
Published2006
Admission routes1
Has abstractyes

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