PARAMETRIC TRAJECTORY OPTIMISATION FOR INCREASED PAYLOAD
Bibliographic record
Abstract
The load-carrying capacity of manipulators is often considered to be the same throughout their workspace. However, the actual capacity of manipulators largely depends on their posture, their velocity, their acceleration and the limits of their actuators. In this paper, a method is proposed to increase the payload capacity of manipulators through trajectory optimisation. This optimisation is performed on a task basis and therefore, the load-carrying capacity varies from task to task. An extensive analysis of the method is conducted based on its application on a planar RR serial two degree-of-freedom manipulator. This analysis evaluates the ability of the method to find feasible trajectories and compares the results with those obtained using Bang-bang type methods. It is shown that, although the trajectories produced by the proposed method are not time optimal, the method is much more versatile and much simpler to implement than its Bang-bang counterparts.
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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 | 0.001 |
| 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".