On the Force Capabilities of Two-Degree-of-Freedom Planar Parallel Mechanisms Equipped With Torque Limiters
Bibliographic record
Abstract
Safety is the most important issue that should be considered when designing collaborative robots that are intended to physically interact with humans. This paper investigates the force capabilities of two-degree-of-freedom planar parallel mechanisms that are equipped with torque limiters (safety clutches). Joint torque limiting devices are used in these mechanisms in order to limit the forces that the robot can apply to its environment. Such devices aim at ensuring the safety of the human beings interacting with the robot. However, because the torque-limiting devices are mounted at the joints of the robot, the end-effector force capabilities induced by these devices are dependent on the pose (Jacobian matrix) of the robot. Therefore, the characteristics of the torque limiting devices must be determined at the design stage in order to ensure safety and maximize effectiveness in all possible poses of the robot. Two types of planar two-degree-of-freedom parallel mechanisms are considered in this paper. Their architecture is first described. Then, the force capabilities are studied based on the Jacobian matrices. The maximum force that can be applied at the end-effector for given torque limits (safety index) is determined together with the maximum isotropic force (effectiveness) that can be produced. The ratio between these two forces, referred to as the force efficiency, can be considered as a performance index. Finally, some numerical results are proposed which can provide insight into the design of cooperation robots based on parallel architectures.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".