Design and Calibration of a Soft Multiple Degree of Freedom Motion Sensor System Based On Dielectric Elastomers
Why this work is in the frame
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Bibliographic record
Abstract
Soft robots use active deformable structures to provide highly capable yet simple and robust robotic systems. Motion sensors for soft robots must, therefore, be able to provide joint position sensing on deformable, multiple degrees of freedom (DOFs) joints often found in soft robot architectures and whose kinematics are not accurately described by closed-form mathematical models. This article proposes a method for designing dielectric elastomer sensor systems for such soft robots. The method is presented as a case study of a soft sensor system for an existing robotic manipulator designed for magnetic resonance image-guided surgery to the prostate. A calibration method based on support vector regression (SVR) is proposed to calibrate the coupled, multi-DOFs sensor system without a model. A prototype sensor system is built and is shown to reach a precision of 0.3 mm root mean square/1.2 mm maximum when calibrated with SVR. These results show sufficient precision for many applications and suggest that model-free calibration is a viable technology for soft robots.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it