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Record W1982904397 · doi:10.1109/iros.2014.6942713

Haptic-enabled teleoperation of base-excited hydraulic manipulators applied to live-line maintenance

2014· article· en· W1982904397 on OpenAlexaff
Vinod Banthia, Yaser Maddahi, Shidin Balakrishnan, Nariman Sepehri

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Line Inspection Robots
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTeleoperationHaptic technologyTeleroboticsSimulationWirelessWorkspaceChannel (broadcasting)ActuatorComputer scienceEngineeringTask (project management)Base stationBase (topology)ReactionRobotMechanical engineeringElectrical engineeringArtificial intelligenceTelecommunicationsMobile robot

Abstract

fetched live from OpenAlex

This paper investigates haptic-enabled teleoperation of a base-excited hydraulic manipulator working under a wireless communication channel. The intended application is live power line maintenance. With respect to this application, three main challenges are recognized in the field: need for the force feedback, wireless communication between master and slave sites, and base excitation of the slave manipulator. In this paper, a test rig is developed to examine how an operator's hand speed regulating scheme enhances the lineman's performance while the entire system works under a wireless communication channel and the slave base is under excitation. Two sets of experiments are performed when the haptic device produces no force and when the regulating haptic force is added to the master device. Performance of the system is evaluated by measuring four indices: operator's failure in completing a task, end-effector displacement, slave manipulator controller effort, and task completion time. Results indicate that adding the haptic force to the system helps linemen function more effectively when the system is subject to base-excitation and communicates through a wireless network.

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)0.000
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.202
Teacher spread0.193 · 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

Citations14
Published2014
Admission routes1
Has abstractyes

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