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Record W4399376544 · doi:10.1061/jaeeez.aseng-5564

Obstacle-Avoidance Safety-Guaranteed Rendezvous Control with a Velocity Safety Corridor and Prescribed Performance

2024· article· en· W4399376544 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

VenueJournal of Aerospace Engineering · 2024
Typearticle
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsObstacle avoidanceRendezvousCollision avoidanceObstacleComputer scienceControl theory (sociology)Control (management)AeronauticsVehicle safetyEngineeringAutomotive engineeringAerospace engineeringComputer securitySpacecraftRobotMobile robotGeographyCollisionArtificial intelligence

Abstract

fetched live from OpenAlex

A novel safety-guaranteed rendezvous control (SGRC) method is proposed for obstacles avoidance during the rendezvous with a noncooperative target in this paper. An artificial potential field with the addition of a velocity safety corridor is used to describe the motion of space and achieve the constraint on the global velocity of the service spacecraft during the rendezvous. Furthermore, the velocity error term of the system is constrained by combining the prescribed performance control (PPC) method, thereby improving the steady- and transient-state performance of the system while reducing fuel consumption. On this basis, a newly constructed virtual auxiliary state containing both artificial potential fields and self-bounded system state error is developed, and a safety-guaranteed control method capable of achieving rendezvous with the noncooperative target for obstacle avoidance is designed. Two sets of numerical simulation results verify the effectiveness as well as the adaptability of the proposed control method.

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.739
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.004
GPT teacher head0.180
Teacher spread0.176 · 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