Design and Control of a 3 Degree-of-Freedom Parallel Passive Haptic Device
Bibliographic record
Abstract
Teleoperated robotic surgery and surgical simulation provide surgeons with tools that can improve the health outcomes of their patients. The limiting factor in many of these systems, however, is the lack of a haptic system that can render high impedance without compromising transparency or stability. To address this issue, we constructed a 3-Degree-of-Freedom haptic device using brakes as actuators. A novel controller is also proposed to increase the range of forces the device can generate and eliminate stiction. The device uses a modified Delta kinematic structure making it light and rigid. Since brakes are intrinsically stable, the device safely generates a wide range of impedance making it well suited for many surgical applications. The novel controller attempts to minimize the sum of forces acting perpendicular to the virtual surface eliminating un-smooth force output and stiction characteristic to passive devices, while increasing the range of displayable forces. The controller was validated using six testing scenarios where it rendered contact with frictionless surfaces. When using the controller, the device rendered the desired surface without stiction. Since the controller successfully rendered complex geometry, it can also work in other applications, such as robotic surgery and surgical simulation.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".