Type synthesis of coordinated multi-robot system based on parallel thought
Bibliographic record
Abstract
For the synthesis of the required type about the multi-robot coordination system in industrial transportation, this paper presents a novel method in which each robot in the coordinated task is viewed as a branched chain of an equivalent parallel robot (EPR), which is converted into a problem for type synthesis of parallel robots. A theoretic method is proposed to represent the kinematic features of the mechanism’s end-effector and its position and pose in the world coordinate system. The basic concept of a robotic characteristic (C) set is given, and the corresponding algorithm is analyzed. Based on the theory of C set, the concrete steps for type synthesis of EPR are presented by analyzing the characteristics of its branched chains, and many EPR groups with end kinematic features for the C sets of the operational tasks are obtained. Then three translational (3T) operational requirements that can be extended to other degrees of freedom (DOF) are adopted, and the DOF of homogeneous and heterogeneous EPR are analyzed using screw theory. Finally the validation of the method is demonstrated by Adams, which shows that the two groups are able to complete the task.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".