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Record W2041260092 · doi:10.1109/icma.2010.5589165

Design and evaluation of a novel flexible bio-robotic foot/ankle based on parallel kinematic mechanism

2010· article· en· W2041260092 on OpenAlexafffund
Qiaokang Liang, Dan Zhang, Quanjun Song, Yunjian Ge

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotic Locomotion and Control
Canadian institutionsOntario Tech University
FundersChina Scholarship CouncilUniversity of Science and Technology of ChinaCanada Research ChairsBattelle
KeywordsKinematicsMechanism (biology)AnkleComputer scienceRobotRobot kinematicsMechanism designFoot (prosody)SimulationEngineeringArtificial intelligencePhysicsMobile robotMathematicsMedicine

Abstract

fetched live from OpenAlex

In this paper, we address the design and evaluation of a novel flexible bio-robotic foot/ankle based on parallel mechanism with three identical UPS prismatic-actuated limbs and a central UR passive limb. After discussing the advantages of using the PKM, the kinematics problem of the PKM are investigated. In particular, to measure the action force at the foot when the bio-robot maintains balance or moves, the cross shaft of the U-joint in the passive limb is modified and intended to be used as an elastic element of the force sensor. Then the development of the integrated force sensor is introduced in detail. The design is helpful for both reliable architecture design and performance improvement of the bio-robot foot/ankle.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0010.000
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 head0.040
GPT teacher head0.260
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations2
Published2010
Admission routes2
Has abstractyes

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