Analytical Modeling and Experimental Validation of a Gelatin-based Shape Sensor for Soft Robots
Bibliographic record
Abstract
Shape sensing of soft robots has been a challenge due to the large deformation of the soft robots and their low stiffness. In this study, a simple yet accurate soft sensor for soft robotic application with small force ranges was proposed, modeled, prototyped, and experimentally validated. The proposed soft sensor is based on a gelatin-graphite composite that exhibited piezoresistive properties. The sensing element was molded to a cylindrical shape and was embedded in a soft flexural structure as a common type of soft flexural robots. Afterward, a mechano-electrical model for predicting the changes in the resistance of the sensing element was proposed and its predictions were validated through an experimental study. To demonstrate usability for force sensing, the sensor was calibrated with a nonlinear model and exhibited a force measurement range of 0.035-0.82N with an average absolute error of 3.7% and a resolution of 4%. Also, the mechano-electrical model was fairly accurate in predicting the piezoresistivity phenomenon of the sensing element under large bending deformations.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".