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Record W3034167006 · doi:10.1109/tro.2016.2597315

Dynamic Point-to-Point Trajectory Planning of a Three-DOF Cable-Suspended Parallel Robot

2016· article· en· W3034167006 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Robotics · 2016
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsWorkspaceTrajectoryPoint (geometry)RobotControl theory (sociology)Point-to-pointParallel manipulatorComputer scienceMotion planningSimulationArtificial intelligenceMathematicsPhysicsGeometryControl (management)

Abstract

fetched live from OpenAlex

This paper proposes a dynamic trajectory planning method for point-to-point motion of three-degree-of-freedom (three-DOF) cable-suspended parallel robots. Natural frequencies as well as associated periodic trajectories that can be obtained from the integration of the dynamic model of an equivalent passive mechanical system are used to design point-to-point trajectories. The trajectories can be used to connect consecutive points in sequence that may lie beyond the static workspace of the robot. The technique ensures zero velocity at each of the target points and continuity of the accelerations. Based on the cable tension constraints, attainable regions can be determined to search for the next target point, while feasible regions of intermediate points are generated in cases for which a given point cannot be directly attained. An example trajectory is performed to illustrate the approach. An experimental implementation is also presented using a three-DOF prototype, and video extensions are provided to demonstrate the results.

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 categoriesMeta-epidemiology (narrow)
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 score0.575
Threshold uncertainty score1.000

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 head0.017
GPT teacher head0.228
Teacher spread0.211 · 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