Combining Thermoelectrics and Low Melting Point Alloys to Create Reconfigurable Stiff-Compliant Manipulators
Bibliographic record
Abstract
Soft robots have garnered great interest in recent years due to their ability to navigate complex environments and enhance safety during unplanned collisions. However, their softness typically limits the forces they can apply and payloads they can carry, compared to traditional rigid-link robots. In this paper we seek to create a hybrid manipulator that can switch between a state in which it acts as a soft robot, and a state in which it has a series of selectively stiffenable links. The latter state, accomplished by solidifying chambers of low melting point metal alloy within the robot, is in some ways analogous to a traditional rigid-link manipulator. It also has the added benefit that each “link” can be set to a desired straight or curved shape before solidification and re-shaped when desired. Thermoelectric heat pumps enable local heating and cooling of the alloy, and tendons running along the robot enable actuation. Using a simple two-link prototype, we illustrate how alloy melting and solidification can be used to modify the robot's workspace and payload capacity.
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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 | 0.000 |
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 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".