Developments toward a hybrid actuated cable-driven parallelmanipulator
Bibliographic record
Abstract
A hybrid cable-driven parallel manipulator (CDPM) is being developed that expands the capabilities of conventional CDPMs by replacing one of the cables with a high packing ratio linear actuator that can be spooled and extended.This actuator uses three curved leaf springs connected using magnetic strips to provide compressive or tensile forces while being very compactly stored, and is kinematically similar to a cable that can push.Conventional CDPMs are useful because they can be lightweight, efficient, have workspaces of hundreds of metres across, and have had accelerations greater than 40G.They are limited in that each of the cables can only produce a tensile force, meaning that in order to function they must have limited forces and accelerations or be configured so that the cables pull against one another antagonistically.By incorporating the extensible linear actuator into the design of a CDPM, the resultant hybrid-actuated manipulator can maintain many of the benefits of standard CDPMs and help overcome their unique challenges.This is being implemented into a 4-actuator pick-and-place manipulator with each of the actuators placed above the workspace in order to help avoid cable interference and ensure that this manipulator could be used in similar spaces as other pick-and-place manipulators like the popular Flexpicker robot created by the ABB (ASEA Brown Boveri) robotics company.
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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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".