GEOMETRIC APPROACH TO SOLVING THE INVERSE DISPLACEMENT PROBLEM OF CALIBRATED DECOUPLED 6R SERIAL ROBOTS
Bibliographic record
Abstract
This paper presents a simple but efficient way to numerically calculate the inverse displacement problem of calibrated decoupled 6R serial robots. The method is iterative and works with any type of calibrated robot model, such as level-3 models, since it requires no algebraic computation and no resolution of high-order polynomials, only the computation of the forward displacement problem of the calibrated robot model and the inverse kinematics of the nominal robot model. The method proposed can find up to eight possible solutions for a given end-effector pose. A numerical example is presented, with one million arbitrary end-effector poses of a level-3 calibrated ABB IRB 120 robot. The computation time for solving the inverse problem is analyzed, and in most cases is found to be only four times the time needed to calculate the nominal inverse kinematics and the calibrated direct kinematics. Furthermore, the method is fast enough to be implemented directly into the robot controller using the RAPID programming language.
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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 | 0.001 |
| 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".