Origami, Shape Memory Alloys, and Geckos? Designing and Manufacturing an Underactuated Self-Reconfigurable Cube Robot
Bibliographic record
Abstract
Modular self-reconfigurable robotic systems are an active field of research leading to versatile, robust, and compact robotic systems. One approach utilizes self-relocatable cuboid robots as building blocks to construct lattice-type modular robotic systems which can be used to construct structures in humanly inaccessible locations through remote or autonomous control. Previous work on self-assembling cube robots has been actuated through both fluidic and inertial methods to provide robot locomotion. The presented robotic cube functions through the harmony of an underactuated Origami Linear Soft Pneumatic Actuator (OL’ SPA) and the modulation of four Shape Memory Alloy (SMA) hinge pin actuators for each face of the cube. By disengaging three of the SMA hinge pin actuators on one of the cube’s faces, the underactuated OL’ SPA expands circumferentially about the remaining engaged SMA hinge pin actuator, opening the cube’s face. Applied to the outside of the outer cube face is a bioinspired gecko tape adhesive, allowing the cube robot the ability to self-reconfigure and climb. Through this innovative integration of novel actuation mechanisms and bioinspired adhesion, the presented robotic cube navigates uncharted terrain in the realm of modular self-reconfiguring robotics.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".