Soft Tactile Skin Using an Embedded Ionic Liquid and Tomographic Imaging
Bibliographic record
Abstract
Whole-body-contact sensing will be crucial in the quest to make robots capable of safe interaction with humans. This paper describes a novel design and a fabrication method of artificial tactile sensing skin for robots. The manufacturing method described in this paper allows easy filling of a complex microchannel network with a liquid conductor (e.g., room temperature ionic liquid (RTIL)). The proposed sensing skin can detect the magnitude and location of surface contacts using electrical impedance tomography (EIT), an imaging technique mostly used in the medical field and examined recently in conjunction with sensors based on a piezoresistive polymer sheet for robotic applications. Unlike piezoresistive polymers, our IL-filled artificial skin changes its impedance in a more predictable manner, since the measured value is determined by a simple function of the microchannel geometry only, rather than complex physical phenomena. As a proof of concept, we demonstrate that our EIT artificial skin can detect surface contacts and graphically show their magnitudes and locations.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".