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Record W4381186310 · doi:10.11159/cdsr23.209

Estimation of Time-Varying Inertia of Aerial Manipulators Performing Manipulation of Unknown Objects

2023· article· en· W4381186310 on OpenAlexaff
Chanhong Park, Alejandro Ramirez‐Serrano, Mahdis Bisheban

Bibliographic record

VenueProceedings of the International Conference of Control, Dynamic systems, and Robotics · 2023
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Vision and Imaging
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceInertiaArtificial intelligenceEstimationComputer visionControl theory (sociology)EngineeringControl (management)Physics

Abstract

fetched live from OpenAlex

This paper presents a method for estimating the varying inertia parameters of unmanned aerial manipulators (UAMs) while they perform manipulation maneuvers on a priori unknown objects and execute various flight maneuvers.The varying mass and moment of inertia tensor of the UAM are estimated using the UAM's force and the kinematic model of its robotic arm by means of a novel sequential Kalman filter (KF) algorithm.In order to validate the effectiveness of the mechanism, it is implemented on a highlymaneuverable VTOL-type UAV equipped with a 3 degree-of-freedom (DoF) manipulator capable of moving only on the longitudinal plane of the aircraft.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.020
GPT teacher head0.262
Teacher spread0.241 · 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 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

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the International Conference of Control, Dynamic systems, and RoboticsSame topicAdvanced Vision and ImagingFrench-language works237,207