A Model-Based Design System for Terrestrial Laser Scanning Networks in Complex Sites
Bibliographic record
Abstract
With the rapid increase of terrestrial laser scanner (TLS) applications, especially for the high-accuracy modelling of large-volume objects, a design system is needed to provide solutions for both scanner and target placement that can meet the project requirements in terms of completeness, precision, economy, and reliability. In this paper, a hierarchical strategy driven by an improved optimization method is developed to solve the TLS viewpoint planning problem. In addition, the placement of the targets is determined by optimizing the target arrangement criterion, and the number of target locations is minimized by accepting the close to optimal target arrangements. Finally, the quality of the design, including the sensitivity of the object coverage to viewpoint placement and the precision of the point cloud are provided. Two building complexes located on University of Calgary campus are used as the experimental datasets in this research. The designs for scanner placement are compared with the “brute force” strategy in terms of the optimality of the solutions and runtime. The results showed that the proposed strategy provided scanning networks with a compatible quality but with more than 80% time savings in design. The number of targets necessary for registration from our system is surprisingly small, considering the volume and complexity of the networks. Through the quality assessments, the sensitivity of the object coverage to the scanner placement indicates how careful the field crew should be when placing the scanner for data capture, and the point cloud precision indicates if the network design can meet the project requirements.
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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".