Model-based Design and Simulation of a Soft Robotic Gripper for Fabric Material Handling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<title>Abstract</title> <italic>Fabric and textile materials are widely used in many industrial applications, especially in automotive, aviation, and consumer goods. Currently, there is a lack of automatic solutions for rapid and effective fabric handling operations that can be expanded to various applications, causing economic loss, workplace safety issues, and process bottlenecks. As a bio-inspired novel technology, soft robotic grippers provide new opportunities for the automation of fabric handling tasks. In this research, an elastomer-based tendon-actuated soft gripper for fabric pick and place tasks is developed through a model-based design approach. Based on finite element analysis, the gripper design is simulated, modified, and validated. Multiple design variables and their impacts are studied. Detailed motion patterns of the underactuated structure are obtained. After the design is established, a prototype is fabricated trough additive manufacturing and overmolding processes to physically test the functionality of the gripper and further validate the simulation results.</italic>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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