Human-in-the-Loop Simulator Study of Remotely Piloted Aerial Systems using Model Mediated Predictor
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2023-2238.vid The presence of time delay in the communication between the ground station and the vehicle in a Remotely Piloted Aerial System (RPAS) is known to reduce overall performance and destabilizes the teleoperation loop. The effectiveness of a model based predictor in mitigating the negative effects of time delays has been demonstrated in fields such as the bilateral teleoperation of telemanipulators, but rarely demonstrated on RPAS. It is known that predictor based approaches rely heavily on the fidelity of the predictor model, but there has been little work showing pilot performance and workload when using different fidelities of predictor model. In addition, the sensitivity of the predictor scheme to unmodeled environmental disturbances has not been thoroughly studied. This paper presents a Model Mediated Predictor (MMP) for delay mitigation, and uses a piloted study to compare the effects of predictor model fidelity, delay time, and turbulence level on pilot performance and workload.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".