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Record W2012105728 · doi:10.1109/biorob.2010.5625949

A 7-DOF haptics-enabled teleoperated robotic system: Kinematic modeling and experimental verification

2010· article· en· W2012105728 on OpenAlexafffund
Simon Perreault, Ali Talasaz, Ana Luisa Trejos, Christopher D. Ward, Rajni V. Patel, Bob Kiaii

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsLawson Health Research InstituteWestern UniversityUniversité Laval
FundersUniversité Laval
KeywordsTeleoperationHaptic technologyKinematicsComputer scienceSimulationReflection (computer programming)TeleroboticsRobot end effectorRobotArtificial intelligenceMobile robotPhysics

Abstract

fetched live from OpenAlex

The purpose of this paper is to demonstrate the development of a novel 7-degree-of-freedom teleoperated robotic system that provides force reflection to the surgeon's hands while performing minimally invasive surgery and therapy (MIST). An endoscopic tool has been sensorized and modified for use as the end effector of this haptics-enabled system. In this paper, mathematical models required for controlling the main components of the system have been determined and experimentally validated. Several experiments have been performed with this MIST robotic system in order to compare its force exertion capabilities with those of the da Vinci system from Intuitive Surgical Inc. Force reflection from the slave to the master in the new system is also demonstrated experimentally.

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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.209
Teacher spread0.199 · 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

Citations7
Published2010
Admission routes2
Has abstractyes

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