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Record W4206998461 · doi:10.1142/s2737480721400057

Adaptive Modeling for Downwash Effects in Multi-UAV Path Planning

2021· article· en· W4206998461 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

VenueGuidance Navigation and Control · 2021
Typearticle
Languageen
FieldComputer Science
TopicDistributed Control Multi-Agent Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDownwashMotion planningPath (computing)CylinderComputer scienceSimulationFlow (mathematics)Aerospace engineeringRobotPhysicsEngineeringArtificial intelligenceMechanicsAerodynamicsMechanical engineering

Abstract

fetched live from OpenAlex

This paper develops a novel method to model the air flow downwash force generated by the quadrotor unmanned aerial vehicle (UAV) and its effect on the neighboring UAVs. Each UAV is shaped by a virtual structure for collision-free path planning. The shape is modified from a standard spherical body to a proposed adaptive cylinder to optimize the path planning while minimizing the downwash impact. The cylinder height varies based on the UAV circumstance and the predicted downwash impact. Furthermore, the downwash model can aid in the cylinder height extreme value appointment. A flock-based path planning algorithm is investigated in this study to compare the spherical UAV shape model with the proposed cylindrical UAV shape model. The UAV with the adaptive cylindrical model is simulated and verified via Gazebo and Robot Operating System (ROS) simulation platform.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score0.713

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 head0.029
GPT teacher head0.280
Teacher spread0.251 · 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