Dynamic Point-to-Point Trajectory Planning of a Three-DOF Cable-Suspended Mechanism Using the Hypocycloid Curve
Bibliographic record
Abstract
This paper proposes a dynamic trajectory planning technique for the point-to-point motion of three-degree-of-freedom cable-suspended mechanisms. The trajectory path is inspired from a hypocycloid curve that is embedded in the plane defined by the acceleration vector at the initial point and the final point. The proposed motion ensures zero instantaneous velocity at each of the endpoints and continuity of the acceleration, while positive cable tensions are guaranteed through a proper choice of the number of arcs of the hypocycloid. The trajectory can be used in sequence to connect consecutive target points that may lie beyond the static workspace of the mechanism. Compared to previously proposed approaches, the technique developed in this paper produces very large regions of attainable target points. In particular, it is proven that horizontal trajectories are always feasible, for any prescribed target point. Simulation results of an example trajectory are included in order to illustrate the approach, along with a video demonstration of an experimental validation performed using a prototype.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".