Development of isomorphic master-slave robots with modular method
Bibliographic record
Abstract
Developed with traditional method, most of the current existing master robots lack of sufficient flexibility and high adaptability to the slave robots, since their structure and degrees of freedom cannot be modified according to those of the slaves. To overcome these shortcomings with the existing master robots, we propose a novel master robot developed with modular method. With the modular approach, it is trivial to build isomorphic master-slave robots according to different tasks. For such isomorphic systems, the mapping between the master and the slave is one-to-one owing to their same configurations, which leads to simple, intuitive and stable control of the slave. In this paper, we introduce the development of the master-slave robotic system, focusing on the design method, the mechanical system, the control system including the hardware and software of the modules, and the communication between the master and slave. An experiment with the master-slave system performing a manipulation task in practice is carried out to illustrate the effectiveness of the presented modular method and the built master-slave system.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".