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Record W4312281527 · doi:10.1109/tmech.2022.3220086

Investigating the Effects of Polynomial Trajectories on Energy Consumption of Quadrotors

2022· article· en· W4312281527 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/ASME Transactions on Mechatronics · 2022
Typearticle
Languageen
FieldComputer Science
TopicDistributed Control Multi-Agent Systems
Canadian institutionsYork University
Fundersnot available
KeywordsPolynomialKinematicsTrajectoryAccelerationEnergy consumptionEnergy (signal processing)Control theory (sociology)Boundary (topology)Polynomial and rational function modelingPower (physics)Monte Carlo methodComputer scienceApplied mathematicsMathematicsPhysicsMathematical analysisClassical mechanicsEngineeringArtificial intelligenceStatistics

Abstract

fetched live from OpenAlex

This article focuses on investigating the effect of quadrotor's trajectory, especially polynomial trajectories, on its energy consumption. First, model-free expressions for power and energy quotients are introduced to relate quadrotor's power and energy directly to its acceleration. This allows to qualitatively estimate quadrotor's energy consumption and compare the effect of different trajectories on energy consumption of identical or different quadrotors independent of quadrotor's manufacturing specifications. Then, polynomial trajectories are analytically investigated for rest-to-rest 1-D scenarios. Scenarios in 3-D with arbitrary kinematic boundary conditions are analyzed via Monte Carlo Simulations with a sample of 10 000 sets of arbitrary boundary conditions. Polynomial trajectories are compared to energy-minimized trajectories in the literature. The results show that increasing the degree of the polynomial increases quadrotor's energy consumption. Moreover, this article suggests using minimum acceleration trajectories as energy-efficient polynomial trajectories. Finally, the results are validated experimentally.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.839
Threshold uncertainty score0.781

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 science0.0010.000
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 head0.013
GPT teacher head0.226
Teacher spread0.213 · 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