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Record W4297193076 · doi:10.3390/drones6100272

Expandable Fully Actuated Aerial Vehicle Assembly: Geometric Control Adapted from an Existing Flight Controller and Real-World Prototype Implementation

2022· article· en· W4297193076 on OpenAlexaff
Chuanbeibei Shi, Kaidi Wang, Yushu Yu

Bibliographic record

VenueDrones · 2022
Typearticle
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsUniversity of Toronto
FundersNational Key Research and Development Program of ChinaState Key Laboratory of Robotics
KeywordsController (irrigation)Payload (computing)SoftwareControl theory (sociology)EngineeringTrajectoryControl engineeringComputer scienceSimulationControl (management)

Abstract

fetched live from OpenAlex

An assembly composed of multiple aerial vehicles can realize omnidirectional motion with six degrees of freedom. Such an assembly has a heavier payload capacity and better fault tolerance compared with a single aircraft. Thus, such assemblies have the potential to become an ideal platform for manipulation. This paper investigates the controller design and prototype implementation for an expandable aerial vehicle assembly (AVA). The proposed AVA is composed of multiple sub-aircraft connected together via spherical joints at their center of mass. Each sub-aircraft can rotate around the spherical joint. The system dynamics of such an AVA can be separated into a slowly varying system and a fast varying system. The design criteria for a controller for this type of AVA was analyzed based on the similarity between the slowly varying system and a fully actuated rigid aircraft. This can reduce the design procedure for the controller and increase the expandability of the AVA. The stability criteria were carefully analyzed by considering the tracking error of each sub-aircraft. As an example, the controller of the AVA was designed using trajectory linearization control on the manifold, since the configuration space of the aircraft is a non-Euclidean space. A prototype composed of three quadrotors was implemented. The real-time expandable communication protocol among the different sub-aircraft was designed based on the CAN bus. Furthermore, the software and the hardware of the real-world prototype were developed. Both simulation and real-world tests were conducted, which validated the feasibility of the control design and the software implementation for an expandable assembly containing multiple aerial vehicles.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.030
GPT teacher head0.308
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2022
Admission routes1
Has abstractyes

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