Foot mounted inertial system for pedestrian navigation
Why this work is in the frame
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Bibliographic record
Abstract
This paper discusses algorithmic concepts, design and testing of a system based on a low-cost MEMS-based inertial measurement unit (IMU) and high-sensitivity global positioning system (HSGPS) receivers for seamless personal navigation in a GPS signal degraded environment. The system developed here is mounted on a pedestrian shoe/foot and uses measurements based on the dynamics experienced by the inertial sensors on the user's foot. The IMU measurements are processed through a conventional inertial navigation system (INS) algorithm and are then integrated with HSGPS receiver measurements and dynamics derived constraint measurements using a tightly coupled integration strategy. The ability of INS to bridge the navigation solution is evaluated through field tests conducted indoors and in severely signal degraded forest environments. The specific focus is on evaluating system performance under challenging GPS conditions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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