A Versatile 3D-Printable Soft Pneumatic Actuator Design for Multi-Functional Applications in Soft Robotics
Bibliographic record
Abstract
Soft pneumatic actuators (SPAs) play a crucial role in generating movements and forces in soft robotic systems. However, existing SPA designs require significant structural modifications to be used in applications other than their original design. The present article proposes an omni-purpose fully 3D-printable SPA design inspired by membrane type mold and cast SPAs. The design features a spring-like zig-zag structure 3D-printed using an affordable 3D printer with thermoplastic polyurethane and a minimum wall thickness between 0.4 and 0.6 mm. The new SPA can perform unidirectional extension (30% extension) and bidirectional (rotation around same axis) bending (100°), with the ability to exert 10 N blocking force for 350 kPa pressure input. In addition, the design exhibits the capability to be scaled down for the purpose of accommodating limited spaces, while simultaneously enabling the reconfigurable interconnection of multiple SPAs to adapt to larger areas and navigate intricate trajectories that were not originally intended. The SPA's ability to be used in multiple applications without structural modification was validated through testing as a robot end-effector (gripper), artificial muscles in a soft tendon-driven prosthetic hand, a tube/tunnel navigator, and a robot crawler.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".