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Record W2327825018 · doi:10.2514/6.2010-8021

A Reconfigurable Robot with Telescopic Links for In-Space Servicing

2010· article· en· W2327825018 on OpenAlexaff
Farhad Aghili

Bibliographic record

VenueAIAA Guidance, Navigation, and Control Conference · 2010
Typearticle
Languageen
FieldEngineering
TopicModular Robots and Swarm Intelligence
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsActuatorKinematicsRobotRobot end effectorParallel manipulatorMechanism (biology)BrakeComputer scienceControl engineeringTrajectoryControl theory (sociology)SimulationEngineeringControl (management)Artificial intelligenceMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

Compacting the arms of a space manipulator in its designated launch volume has been a difficult design problem in several robotic missions not only for in-orbit servicing but also for planetary exploration. This paper presents a conceptual design for space manipulators with lockable telescopic links that allows the arms to change their length as well as the twist angles. Each cylindrical telescopic link is equipped with a built-in brake mechanism which is normally locked, but the lock can be released whenever the kinematic parameters are to be changed. Since the telescopic links do not have any actuator, the robot reduces its number of degrees of freedom by constraining the motion of its end-effector in order to be able to control the values of the length and the twist angles. The control system which autonomously realizes the configuration change in addition to autonomous calibration of the manipulator after every configuration change are fully developed in this work. Several space mission examples which can benefit from such a reconfigurable robot are 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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 science0.0000.000
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 head0.008
GPT teacher head0.212
Teacher spread0.204 · 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
Published2010
Admission routes1
Has abstractyes

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Same venueAIAA Guidance, Navigation, and Control ConferenceSame topicModular Robots and Swarm IntelligenceFrench-language works237,207