3D Shrinking for Rapid Fabrication of Origami-Inspired Semi-Soft Pneumatic Actuators
Bibliographic record
Abstract
Soft actuators are an essential component of soft robots. They are also well suited for human-friendly robots due to their intrinsic safety. The advantages of origami structures have motivated the development of origami-inspired semi-soft actuators. In this paper, a novel rapid, systematic and cost-effective fabrication method for durable origami-inspired semi-soft pneumatic actuators is presented. The proposed method employs heat-shrinkable polymers conforming to reusable molds. It is applicable to a variety of origami patterns, and it produces actuators with consistent performance. Two origami semi-soft pneumatic actuator designs (accordion and Yoshimura patterns) have been fabricated. Each actuator was fabricated in less than 10 minutes (not including the time required to create the molds and plastic components). A nonlinear finite-element model is developed to predict the actuator's folding behavior and blocked force. The results show that it can predict the blocked force with a maximum error of 5.7% relative to experimental measurements. This model can be used to improve the design of future actuators. Experimental results for isometric, isobaric, isotonic and cyclic fatigue tests for the accordion pattern actuator are included and discussed. The actuator prototype has a maximum stroke of 40 mm (or 36% of its effective length) and a maximum blocked force of 124 N at a vacuum pressure of -80 kPa. It also showed no decrease in performance and no leakage after 1000 cycles with a payload of 0.9 kg, demonstrating its durability compared to previous origami-inspired semi-soft pneumatic actuators. Finally, it has a high force-to-weight ratio as it can lift a load more than 118 times its own weight. Its performance demonstrates that powerful, lightweight and durable actuators can be easily produced by the proposed fabrication method.
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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".