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RESOLVE REDUNDANCY WITH CONSTRAINTS FOR OBSTACLE AND SINGULARITY AVOIDANCE SUBGOALS

2008· article· en· W2056782819 on OpenAlexvenueno aff
Ciyuan Qiu, Qixin Cao, Yu Sun

Bibliographic record

VenueInternational Journal of Robotics and Automation · 2008
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsObstacleRedundancy (engineering)Obstacle avoidanceComputer scienceSingularityArtificial intelligenceMathematicsGeometryPolitical scienceOperating systemLaw

Abstract

fetched live from OpenAlex

In this work we analyse the general form solution of the Inverse Redundant Kinematics (IRK) problem from a geometric point of view. We propose two new methods, Velocity Projection Constraints Method (VPCM) and On-line Task Modification Method (OTMM), which formulate the obstacle and singularity avoidance as constraints, and will be incorporated in the standard Quadratic Programming (QP) method to resolve the IRK problem. This will avoid the compromise or conflict between weighted optimization criteria for the obstacle and singularity avoidance subgoals, as well as the complicated weight adjustment process. The OTMM is effective not only to redundant manipulators but also to nonredundant manipulators. Numerical simulation examples validate and prove the effectiveness of the proposed methods.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.518
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 head0.011
GPT teacher head0.219
Teacher spread0.208 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2008
Admission routes1
Has abstractyes

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