Series Clutch Actuators for safe physical human-robot interaction
Bibliographic record
Abstract
This paper presents the design, implementation and control of a device intented to mechanically improve the safety of serial robots interacting with humans. The device consists of an electronically adjustable torque limiter placed in series with each actuator, referred to as a Series Clutch Actuator (SCA). By appropriately adjusting the limit torques according to the robot's configuration, the maximum static force that the robot can apply to its environment at the Tool Centre Point (TCP) can be limited to a prescribed safe level. If a limit torque is exceeded, the SCA slips and an emergency stop is triggered while the inertia located upstream from the SCA in the kinematic chain is mechanically disconnected. A method is presented to determine the optimal limit torques that maximize the isotropically achievable force (which can be applied in all directions without triggering any SCA) while satisfying the safe force limit. An approach to optimize the pose of a redundant robot in order to maximize the isotropically achievable force while preserving a safe maximum force threshold is also proposed. The design and fabrication of a torque limiter using a large number of friction discs is presented. Finally, the mechanisms are implemented into a 4-DOF redundant serial arm and preliminary experimental results are presented.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".