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Record W1916203309 · doi:10.1109/cira.2001.1013170

Are parallel manipulators more energy efficient?

2002· article· en· W1916203309 on OpenAlexaff
Yan Li, Gary M. Bone

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsWorkspaceParallel manipulatorSerial manipulatorEfficient energy useMobile manipulatorAccelerationPower (physics)Computer scienceEnergy (signal processing)Control theory (sociology)Position (finance)Robot end effectorSimulationRobotAutomotive engineeringMobile robotEngineeringElectrical engineeringArtificial intelligencePhysicsControl (management)

Abstract

fetched live from OpenAlex

The energy efficiency of a robotic manipulator is important, particularly when that manipulator is used in conjunction with a mobile robot with limited battery life. In the paper the energy efficiency (in terms of the electrical energy usage) of a spatial three DOF parallel manipulator is compared to a serial manipulator with the same drive motors and a similar workspace. The effects of end-effector position, velocity and acceleration, and static loading due to gravity are examined. Over a range of conditions, the average energy usage of the parallel manipulator was determined to be 26% of the serial manipulator's. This benefit is not due simply to the reduction in moving mass achieved by the parallel design since its moving mass is 70% of the serial manipulator's. Static loading due to gravity was found to roughly double the power usage of both manipulators without significantly affecting their relative energy efficiency.

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: none
Teacher disagreement score0.944
Threshold uncertainty score0.786

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)0.0010.000

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 head0.016
GPT teacher head0.182
Teacher spread0.166 · 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

Citations40
Published2002
Admission routes1
Has abstractyes

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