Fabrication and characterization of a pneumatic soft gripper integrated with a novel 3D-printed piezoresistive force sensor
Bibliographic record
Abstract
Abstract A pneumatic soft gripper, composed of multiple elastomeric materials, was designed and manufactured based on gripping simulations. The simulation results demonstrated that the different stiffnesses of the elastomeric materials can influence the internal air pressure required for the proper actuation of the gripper. Considering the substrate properties and the morphological changes of the soft gripper during gripping, a piezoresistive force sensor was developed using elastomers and conductive filaments with the aid of additive manufacturing techniques. We confirmed the reproducibility and stability of the proposed piezoresistive force sensor through evaluations under various fabrication conditions. Results from touch experiments and compressive force measurements indicated that the stiffness of the sensor substrate and the thickness of the conductive part of the sensor affected the sensitivity and reliability of the sensor with respect to different levels of applied forces. Incorporating a rigid panel between the soft gripper and the piezoresistive force sensor diminished the effect of the variable stiffness and curvature of the gripper on the measurement of electrical resistance generated by the piezoresistive force sensor. Our 3D-printed sensor combined with elastomeric materials showed the possibility of differentiating the simple actuation and the gripping demonstration of the soft gripper.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".