Vertical Pipe Inspection Using Swarm of Independent Robots
Bibliographic record
Abstract
The work reported here describes a solution to the problem of inside vertical pipe inspection using a swarm of independent mobile robots. The proposed solution assumes the pipe diameter to be known, however, it does not make any further assumptions concerning the height to be climbed/inspected or the material and characteristics of the pipe. The robots considered are fully independent/intelligent/autonomous units and are able to connect to each other firmly as needed so as to form diverse rigid configuration structures (swarms). By exploiting the rigidity of such connections, the robots composing a swarm climb the inner vertical walls of a pipe simply by exerting together a force towards the pipe walls and by jointly moving forward at the same speed (as a team). During the joint motion, the robots are able to monitor their peers as well as the integrity of the surface by using a small CCD camera mounted on top of each robot. If one of them detects an unusual condition, it lits up and continues its motion waiting for all the other to acknowledge the situation by litting up them-selves. When this happens, they all jointly stop preventing in this way a sudden break of the force exerted on the walls and a consequent collapse of the swarm structure. In this way diverse pipe configurations can be effectively inspected.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".