Trajectory planning method for UAV inspection of transmission towers based on simulated annealing algorithm
Why this work is in the frame
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Bibliographic record
Abstract
Efficiently planning the trajectory of unmanned aerial vehicles (UAVs) for power grid inspections is a critical factor in ensuring the performance of such inspections and represents a current research hotspot in the field of UAV-based power grid inspections. In this study, addressing the limitations of traditional algorithms in meeting the requirements of UAV inspections, we propose a multi-objective Traveling Salesman Problem (TSP) optimization model. This model aims to optimize the UAV trajectory while considering both speed and prioritizing visits to towers with multiple defects. The simulated annealing algorithm is employed to solve this optimization problem and implement it through MATLAB programming. The results show that the path distance obtained after applying the algorithm converges more effectively towards the optimal solution. This demonstrates the effectiveness of the proposed algorithm in addressing the optimization challenges related to UAV-based inspection trajectories.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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