DESIGN AND IMPLEMENTATION OF AN INDOOR LOCALIZATION SYSTEM FOR THE OMNIBOT OMNI-DIRECTIONAL PLATFORM
Bibliographic record
Abstract
The design and implementation of an indoor absolute localization system for a novel three-degree-of-freedom (DOF) omni-directional mobile platform is presented. This localization system is a modification of the Cricket indoor localization system developed at the Massachusetts Institute of Technology (MIT) and is similar to the Global Positioning System (GPS) used in outdoor applications. The designed system has an active mobile architecture with actively transmitting beacons mounted on the mobile platform, and receivers (listeners) fixed at known positions on the ceiling of the operating environment. Position estimates of the mobile beacons, relative to a global coordinate system, are obtained using trilateration; a technique that determines the position of a beacon using distance estimates between the beacon and the fixed listeners. The distance estimates between the beacons and listeners are calculated using the time-of-flight of radio frequency and ultrasonic signals. Testing of the localization system was performed and experimental results are presented. These preliminary results indicate that the modified Cricket system has improved accuracy in distance and position estimation compared to the original system, as well as a higher position update rate when performing tracking of the mobile platform.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".