Design and Validation of an Origami Paper-Based Gripper
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
Abstract The present research introduces an innovative, cost-effective approach to robotic gripper design, utilizing origami-based engineering to overcome the complexities and high costs associated with conventional grippers. We developed a lightweight origami gripper that transitions from a square to a rhombus shape through simple manual folding. This type of device has certain features depending on how folding lines are placed, design parameters, folding orientation, and material thickness. This transformation enables efficient grasping and gap bridging, a significant advancement over the limited capabilities of traditional paper-based origami grippers. The proposed gripper was tested in two different materials, namely, cardstock paper and plastic sheet, both of which were able to hold most common objects properly such as a stuffed toy, phone stand, bottle cap, wine cork, magic cube, and similar-sized items. However, in terms of lifted weight, the plastic gripper performed better during the lifting tests which were performed using a bottle of water, a scale, and identifying the maximum weight it can hold. A key aspect of our research is the geometric analysis of the gripper’s transformation, focusing on how the control angle influences the gripper’s final shape and functionality. An analytical model was developed to figure out how manual folding, specifically the angular displacement input, moves each folding line in the origami and establishes three types of folding lines in the presented origami which are valley, mountain, and contour lines. After this process, some equations were calculated to characterize this motion working with three major angle parameters alpha, beta, and gamma. The present research validates the proposed origami gripper in three major aspects; analytical modeling using angular parametric equations, computational simulation performed using Rigid Body Dynamics (RBD) as well as the lifting weight experiment to evaluate its limitations. The experimental test confirms what the theoretical analysis and computational simulation outlined regarding the predicted motion and maximum angle it can reach to close the gap. Moreover, the simulation showed and quantified critical stress zones across the origami, which are the side internal corners for the lifting experiment modeled as a sliding force. Through this investigation, we encapsulated the interplay between these parameters mathematically, enhancing our understanding of the gripper’s mechanics. Our theoretical and simulation results closely align with mathematical predictions, confirming the practicality of this design. The proposed origami gripper, with potential enhancements and an appropriate actuation mechanism, presents a promising solution for efficient, lightweight robotic grippers in various applications.
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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 | 0.001 | 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