Remote sensing and analysis using autonomous mobile robot with onboard micro-spectrometer
Bibliographic record
Abstract
There has been an increasing interest in remote sensing and analysis of the environment. The applications include disaster monitoring, exploration, and natural resource protection. However, the human operation is labor intensive, time consuming and hazardous. The sensors fixed on-site in the environment suffer from limited sensing coverage and still requires human's on-site installation and maintenance. This paper proposed a novel system for the remote sensing and analysis of the environment using a mobile robot with on-board micro-spectrometer. A tracked locomotion is designed to adapt to tough terrains. The FLC (fuzzy logic control) navigate the mobile robot traversing trough the environment and collects the samples. The onboard micro-spectrometer system senses the samples and pattern of the solution spectrum is recognized through the ANN (artificial neural network). The results show the system can effectively and efficiently sample and classify several nominal solutions. The robot successfully transmits the spectrum and analysis to the remote control station through the proposed distributed architecture. The proof-of-concept demonstrates an unmanned operated chemical lab in motion for the remote sensing and analysis of the environment by integrating the micro-spectrometer with the autonomous mobile robot.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".