3-DOF Cartesian Force Limiting Device Based on the Delta architecture for safe physical human-robot interaction
Bibliographic record
Abstract
This paper presents a device that significantly improves the safety of ceiling-mounted robots whose end effector orientation remains constant with respect to the vertical direction (e.g. Scara-type robots). The device consists of a three-degree-of-freedom (DOF) parallel mechanism with the Delta architecture on which the revolute actuators have been replaced with torque limiters. The resulting Cartesian force limiting device (CFLD) is implemented as a mechanical connection between the robot and the effector. It is rigid unless excessive forces are applied on the end effector, for example during a collision. The magnitude of force that activates the mechanism is set by properly adjusting the threshold of the torque limiters. Furthermore, a collision can be rapidly detected with a limit switch placed on one of the links of the mechanism and a signal can be sent directly to brakes that will stop the robot, without passing through a controller and thus improving the reliability and reaction-time of the safety system. By mechanically disconnecting the robot from its end effector, the device ensures that the person involved in the collision is only subjected to the inertia of the end effector and thus potential injuries are greatly reduced. This work is the extension of a previous 2-DOF CFLD that was sensitive only to horizontal forces. The new architecture reacts to collisions occuring in any direction and is geometrically optimized for the proposed application. Also, means to achieve gravitity compensation are proposed.
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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) | 0.000 | 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 | 0.001 |
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".