Investigation of Dynamic and Control of Robots’ Cooperation in Assembling Process
Bibliographic record
Abstract
Assembling and fitting parts together can be considered as one of the most practical but also challenging process in robotics. Various applications are conceivable such as spatial ones where accessibility is reduced or in construction fields where huge forces have to be dealt with in a meticulous manner. In this paper, the cooperation of two robots during the complete assembling process of two structural parts from the approaching phase to the fitting stage is investigated. In the approaching phase for taking the parts closer, the two large construction parts may collide due to the inertia of motion, causing considerable impact forces even with the slightest relative velocity. This issue presents important control challenges as the effects of this local impact may be transferred throughout the system’s frame, affecting all other elements and inducing instability. Finally after connection of these two parts is established, the whole frame is transported to any desired location by cooperative operation of the two robots. Each step requires a particular controller to deal with different system’s dynamics that occur during the whole process.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".