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Record W2409593918 · doi:10.1109/icra.2016.7487435

Development and experimental validation of a reorientation algorithm for a free-floating serial manipulator

2016· article· en· W2409593918 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsRevolute jointSerial manipulatorRobotTrajectoryControl theory (sociology)Computer sciencePlanarActuatorRotation (mathematics)Motion planningNonlinear systemAlgorithmParallel manipulatorSimulationArtificial intelligenceControl (management)Physics

Abstract

fetched live from OpenAlex

This paper presents a method to reorient a free-floating serial manipulator using internal motion based on a path planning algorithm using a dynamic model of the manipulator and a potential function. Simulations with the proposed algorithm are performed using a nonlinear optimization technique in order to determine the actuator's velocity trajectories that achieve the reorientation. An example trajectory is presented in which a three-link planar robot starts from a pose in which all the links are aligned and ends with the same joint configuration but with the robot having completed a 180 degrees rotation. For this example, the algorithm finds trajectories that allow the robot to complete approximately 94% of the reorientation. To verify the simulation results against a real robot, a prototype of a planar robot with three bodies and two revolute joints is built. The experiments conducted show that the prototype is able to achieve the prescribed reorientation, even though the control of the orientation was implemented in an open-loop mode.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.687
Threshold uncertainty score0.244

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 head0.031
GPT teacher head0.277
Teacher spread0.246 · 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

Quick stats

Citations9
Published2016
Admission routes1
Has abstractyes

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