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Record W4411744189 · doi:10.1007/s13272-025-00861-y

Relative kinematics for a jerk-level trajectory generation system

2025· article· en· W4411744189 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

VenueCEAS Aeronautical Journal · 2025
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
FundersTechnische Universität München
KeywordsJerkKinematicsTrajectoryControl theory (sociology)PhysicsComputer scienceClassical mechanicsArtificial intelligenceAcceleration

Abstract

fetched live from OpenAlex

Abstract Using electric vertical takeoff and landing (eVTOL) aircraft for urban air mobility requires a high level of maneuverability and tracking accuracy from the flight guidance systems. This can be achieved by constructing a high-order desired trajectory, in order to provide jerk-level feedforward commands and acceleration-level relative kinematics. In this paper, we perform a noise analysis on a trajectory system where relative kinematics are computed numerically, and we show the resulting noise effects. We then present an analytical alternative which improves the noise sensitivity. Additionally, we develop a smoothing strategy for obtaining a high-order parametrization of a trajectory designed with low-order clothoid curves. The methods presented in the paper are tested and validated in closed-loop simulations and through flight tests on a 700 kg medical-evacuation eVTOL aircraft. The results of these tests are presented and discussed.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.778
Threshold uncertainty score0.494

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 head0.034
GPT teacher head0.250
Teacher spread0.216 · 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