Design of a Soft Multi-Degree of Freedom Tool Positioner With Variable Stiffness Integrating Molded Air Muscles Actuation, Granular Jamming and Dielectric Elastomer Sensing
Bibliographic record
Abstract
Soft technology is more and more present in robotics allowing safe interaction with humans, high dexterity in constrained environments, and safe manipulation of fragile or undefined objects. However, soft robotics is limited by a fundamental trade-off between available workspace and stiffness. Position feedback is also challenging as soft robots generally use deformable mechanisms instead of discrete joints. Here, the design of a soft four-degree-of-freedom tool positioner integrating a brake system and a soft sensor is proposed to address these issues. The design integrates molded air muscle actuators, granular jamming brakes, and Dielectric Elastomer Sensors (DES). The design is experimentally validated based on the requirements of a manipulator for liver cancer treatment, which is a representative application of soft robotics. The use of granular jamming mitigates the fundamental trade-off of soft robotics as it allows the manipulator to reach a large workspace (1500 cm3) while having the capacity to provide a high stiffness (up to19 times the initial stiffness). DES provides satisfactory position feedback, demonstrating a 0.69 mm accuracy that is lower than the 1 mm requirement. The proposed design using granular jamming and DES could greatly benefit human-safe and medical robotics.
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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".