Planning of Mobile Crane Walking Operations in Congested Industrial Construction Sites
Why this work is in the frame
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Bibliographic record
Abstract
The trend toward more compact designs and congested site layouts makes it challenging for lift planners to provide feasible lift paths for mobile cranes, confronting the added risk of potential collisions when maneuvering through on-site obstacles. In some cases, particularly in congested industrial modular projects, it is inevitable for mobile cranes to walk with loads to a position with sufficient clearance to perform the lifts and place the objects in their final set position. This study contributes to the body of knowledge by introducing a comprehensive lift planning framework to plan complicated lifts involving mobile crane walking operations. Due to the lack of reliable and accurate plans for such lifts in practice and the added complexities, they are often eluded by practitioners compared with the more straightforward pick-and-set scenarios. This study proposes an algorithm for optimized planning of crane walking–involved lift operations borrowing an obstacle avoidance technique from robotics. The proposed path planner thoroughly considers site constraints and crane configurations to prevent collision between the crane body and the load with preinstalled objects. Actual case studies are presented to validate the efficiency of the proposed algorithm. The system generated the presented real-world lift in less than 5 min, satisfying the operations’ optimality, safety, and feasibility.
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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 | 0.001 | 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