ALLFlight: multisensor data fusion for helicopter operations
Bibliographic record
Abstract
The objective of the project ALLFlight (Assisted Low Level Flight and Landing on Unprepared Landing Sites) is to demonstrate and evaluate the characteristics of different sensors for helicopter operations within degraded visual environments, such as brownout or whiteout. The sensor suite, which is mounted onto DLR's research helicopter EC135 consists of standard color or black and white TV cameras, an un-cooled thermal infrared camera (EVS-1000, Max-Viz, USA), an optical radar scanner (HELLAS-W, EADS, Germany) and a millimeter wave radar system (AI-130, ICx Radar Systems, Canada). Data processing is designed and realized by a sophisticated, high performance sensor co-computer (SCC) cluster architecture, which is installed into the helicopter's experimental electronic cargo bay. This paper describes applied methods and the software architecture in terms of real time data acquisition, recording, time stamping and sensor data fusion. First concepts for a pilot HMI are presented as well.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".