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Record W2005010226 · doi:10.1177/0278364907076819

Manipulation of Convex Objects via Two-agent Point-contact Push

2007· article· en· W2005010226 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

VenueThe International Journal of Robotics Research · 2007
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPoint (geometry)ControllabilityComputer scienceObject (grammar)Position (finance)Regular polygonOrientation (vector space)Control theory (sociology)RobotComputer visionArtificial intelligenceSimulationControl (management)MathematicsGeometry

Abstract

fetched live from OpenAlex

This paper explores a sensorless manipulation method for orienting and translating convex objects in the plane. The manipulation task is performed by a two-agent point-contact push. During the manipulation, each agent makes a point contact with the object, and both agents push together along a straight-line. One advantage of the two-agent point-contact push over the physical fence based push is that the two-agent point-contact push can manipulate non-polygonal parts, and reduce the position and orientation uncertainties simultaneously. First, two manipulation primitives are identified, equilibrium and non-equilibrium pushes, and the motion of the object characterized under these two pushing actions. Then, a controllability analysis is conducted for this class of manipulation using the theory of positive bases. After the analysis, the planning problem is studied in the framework of a switched system, and an analytical solution to the planning problem is developed. Finally, manipulation examples and experiments are provided to demonstrate the proposed manipulation 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)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.678
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0010.000
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 head0.078
GPT teacher head0.372
Teacher spread0.294 · 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