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Record W4239741698 · doi:10.1115/detc2015-46486

Force Capabilities of Two-Degree-of-Freedom Serial Robots Equipped With Passive Isotropic Force Limiters

2015· article· en· W4239741698 on OpenAlexaff
Meiying Zhang, Thierry Laliberté, Clément Gosselin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsIsotropyRobotLimiterTorquePlanarContact forceRobot end effectorControl theory (sociology)Computer scienceEngineeringSimulationPhysicsElectrical engineeringClassical mechanicsArtificial intelligenceControl (management)

Abstract

fetched live from OpenAlex

This paper proposes the use of passive force and torque limiting devices to bound the maximum forces that can be applied at the end-effector or along the links of a robot, thereby ensuring the safety of human-robot interaction. Planar isotropic force limiting modules are proposed and used to analyze the force capabilities of a two-degree-of-freedom planar serial robot. The force capabilities at the end-effector are first analyzed. It is shown that, using isotropic force limiting modules, the performance to safety index remains excellent for all configurations of the robot. The maximum contact forces along the links of the robot are then analyzed. Force and torque limiters are distributed along the structure of the robot in order to ensure that the forces applied at any point of contact along the links are bounded. A power analysis is then presented in order to support the results. Finally, examples of mechanical designs of force/torque limiters are shown to illustrate a possible practical implementation of the concept.

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)0.000
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 score0.196
Threshold uncertainty score0.507

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 head0.242
Teacher spread0.201 · 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 designSimulation or modeling
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

Citations0
Published2015
Admission routes1
Has abstractyes

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