Distributed UWB-Aided Cooperative Positioning with Height Constraints for Multi-AGV Systems in Gnss Challenged Conditions
Bibliographic record
Abstract
This paper proposes a distributed cooperative positioning (CP) framework for autonomous ground vehicle (AGV) clusters operating in Global Navigation Satellite System (GNSS) challenged conditions. Each AGV performs local state estimation using GNSS/Inertial Measurement Unit (IMU) measurements and exchanges only position and covariance information with neighboring nodes to minimize communication load. Inter-node Ultra Wide Band (UWB) ranging and a height constraint are incorporated into a distributed Kalman filter to enhance network observability and ensure stable positioning. Real-world experiments with a multi-AGV platform demonstrate that the proposed framework achieves superior positioning accuracy and robustness compared with the centralized method. Moreover, the inclusion of the height constraint effectively improves local geometric configuration and reduces Geometric Dilution Precision (GDOP), leading to more consistent and reliable positioning performance for GNSS-limited nodes within the cooperative network.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".