A cooperative UAV/UGV platform for wildfire detection and fighting
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) have received much attention in the research and development community due to their strong potential in certain high-risk missions. In applications that involve multiple vehicles, the inter-vehicle communication and cooperation becomes a critical challenge to a successful mission. An effective co-operative control framework is required to co-ordinate the system-level decision making process and information flow among the multiple agents such that the collective mission is optimally achieved. In this paper, a cooperative control framework for a hierarchical UAV/UGV platform is proposed. A top-level mobile mission controller provides effective mission planning and system-level decision making such that mission completion time and resource expenditure are optimized. The mobile mission controller can monitor the dynamic environment with its own sensing capabilities and coordinate UAVs/UGVs in their actions. This paper discusses the potential application of the proposed hierarchical vehicle platform to high-risk missions, specifically in the context of wildfire fighting. The task generation and allocation problems and proposed approaches are presented under the given control framework.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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