PRIMUS: SWAP-oriented IMUs for multiple applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In many applications, Size, Weight and Power (SWAP) consumption are key drivers in the design of a gyrocompass. During the past decade, Safran Electronics & Defense (formerly known as Sagem) designed the Hemispherical Resonator Gyroscope (HRG), a low-size, low-weight and low-power consumption sensor with remarkable performance to achieve efficient North Finding and Keeping (NF/NK), but also navigation-based applications. Taking the most out of HRG's outstanding reliability by design, Safran is now manufacturing a whole IMU product line, based on its high-end vibrating gyro, associated with MEMS accelerometers and a miniaturized electronic board. Through a SWAP-oriented design, Primus inertial measurement units are able to fulfil the needs of a wide range of navigation applications. Indeed, navigation systems based on Primus IMUs have already demonstrated: i) Sub-mil North and vertical finding accuracy, for many applications, including e.g. targeting ii) Sub-Metric inertial (GNSS-free) position keeping for cartography and mapping applications iii) State of the art accuracy for land and marine navigation systems iv) Easy integration into a navigator, thanks to Primus' multiple interfaces (GPS, DVL, CAN Bus, odometer, barometer ...). This paper introduces the Primus IMU and presents: v) An overview of Safran's work on the Hemispherical Resonator Gyroscope vi) Characteristics of the Primus IMU product line: a SWAP-focused architecture vii) Examples of applications addressed by Primus IMU.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it