An Ultrasonic and Vision-Based Relative Positioning Sensor for Multirobot Localization
Why this work is in the frame
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Bibliographic record
Abstract
This paper proposes a novel 3D sensor node to establish relative measurements within a robot network. The developed sensor nodes employ ultrasonic-based range measurement and infrared-based bearing measurement for spatial localization of robots. The sensor is low power, lightweight, low cost, and designed to be applicable across many robotic platforms, including microaerial vehicles. The proposed sensor design requires only two robots to perform relative measurements of each other and achieves a measurement accuracy of 0.96-cm Root-Mean-Square Error (RMSE) for range and 0.3° RMSE for bearing. The sensor nodes are scalable and can be configured using either Star or Mesh protocols with a maximum of 10-Hz update rates over a detection range of 9 m. The correspondence issue of having multiple robots is resolved using time division multiple access methods where different time slots are used by each sensor node. These features are verified by multiple experimental evaluations on a multirobot team with both ground and aerial agents. The proposed approach allows multirobot localization in scenarios where supportive positioning services such as GPS are unavailable. As a result, even basic robots, which lack powerful simultaneous localization and mapping capabilities, will be capable of autonomous navigation by accessing the positional information provided by the sensor network.
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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 | 0.000 | 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