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Record W2335724010 · doi:10.1061/40476(299)8

Canadian Space Robotic Development for Planetary Exploration

2000· article· en· W2335724010 on OpenAlexaffabout
C. Sallaberger, James A. Middleton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsSpace explorationMars Exploration ProgramPlanetary explorationSystems engineeringRoboticsInternational Space StationSpace (punctuation)Space technologyAutomationSpace ShuttleEngineeringSpace researchComputer scienceAgency (philosophy)RobotPlanetary surfaceExploration of MarsAerospace engineeringArtificial intelligenceAstrobiologyMechanical engineeringOperating system

Abstract

fetched live from OpenAlex

Canada has invested over $1.4B during the past 25 years in the development of robotic manipulator systems for the Space Shuttle and Space Station Programs. Mars, Moon and other bodies in our solar system are seen as an excellent opportunity to utilize this established advanced space robotic capability as a base for continued robotics technology development and utilization. Coupled with a strong interest from the Canadian planetary science community, and the recent launch of a new Space Exploration Program by the Canadian Space Agency, this has lead to some exciting robotic development activities to utilize this capability to support Canadian participation in planetary missions. This paper gives an overview of these activities including identification of near-term international planetary missions expected to use Canadian robotic manipulators, design reference tasks for the robotic activities, new design methodologies, hardware prototyping activities, leapfrog technology thrusts, together with automation and reliability issues.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.856
Threshold uncertainty score0.993

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)0.0010.000

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 head0.010
GPT teacher head0.170
Teacher spread0.160 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations1
Published2000
Admission routes2
Has abstractyes

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