Wireless Control of a Teleoperated Hydraulic Manipulator With Application Towards Live-Line Maintenance
Bibliographic record
Abstract
This paper presents the procedure of establishing performance charts for effective utilization of a teleoperated hydraulic manipulator working under wireless communication channels. A teleoperated system, comprising a master haptic device and an industrial hydraulic manipulator, is constructed. The master and slave communicate through a communication channel emulated using the NS2 simulator. Two sets of experiments are designed to construct performance charts that guide us to select appropriate parameters of wireless network setup by which a particular value of position error appears at the slave hydraulic manipulator end-effector. The network parameters are: configuration of environment obstruction, transmission power of the router, and distance between the master and slave sites. The first set of experiments is conducted to define three regions of tracking quality, and to construct the performance charts. The second set of experiments confirms satisfactory performance, when the teleoperated system is located within the recommended regions in the established charts. One application of this study is live-line maintenance using remotely-operated hydraulic manipulators.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".