The sequential framework for developing motion planners for many degree of freedom manipulators: Experimental results
Bibliographic record
Abstract
A sequential framework that allows planners for manipulator arms with many degrees of freedom to be developed is addressed. The essence of this framework is to exploit the serial structure of manipulator arms and decompose the n-dimensional problem of planning collision-free motions for an n-link manipulator into a sequency of smaller m-dimensional subproblems, each of which corresponds to planning the motion of a subgroup of m-1 links. Extensive experimental results within the sequential framework are presented for a variety of manipulators. A main goal of these simulations (1) to show the effectiveness of the sequential approach with the backtracking mechanism, and (2) to quantify the improvement of the backtracking mechanism and the trade-off between the number of backtrackings and the execution time of the planner. The experiments show that the sequential framework with the backtracking mechanism is quite efficient for manipulator arms with many degrees of freedom.
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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 | 0.001 | 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".