Parameters Identification of the Path Placement Optimization Problem for a Redundant Coordinated Robotic Workcell
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Bibliographic record
Abstract
This paper proposes a method to identify the number of independent parameters in order to optimize the placement of a given path for a coordinated redundant robotic workcell. The workcell consists of a generic 6 DoF serial manipulator and a 1 DoF redundancy provider (RP). The RP is not attached to the serial manipulator, but the workpiece is attached to the RP. Two cases of RPs are investigated, namely a rotary table and a linear guide. In general, 6 parameters are needed in order to place a path on the RP, and 6 parameters to place the RP in the workspace of the serial manipulator. However, because of the symmetricities and the degree of redundancy involved in the problem, not all 12 parameters can independently affect the placement operation. Therefore, it is important to identify the number of independent parameters in order to improve the efficiency of the placement optimization process. This paper presents an innovative method for determining the number of independent parameters for both cases under study, i.e., the rotary table and the linear guide, with and without considering each one’s joint limits. The optimization process is briefly introduced and the results of using all 12 parameters, as opposed to only the independent ones, are compared. Finally, the performance of the rotary table is compared to the linear guide, for a sample path.
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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 it