Pose optimization and path improvement in robotic drilling through minimization of joint reversals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Industrial robots have been increasingly adopted in precision manufacturing applications such as aerospace drilling. However, achieving the strict tolerance requirements of the aerospace industry has been a major challenge due to the relatively poor accuracy of robots. One of the major sources of error which has a detrimental effect on the quality and circularity of drilled holes is the static friction in robot joints. These errors are particularly pronounced when one or more joints reverse direction. To improve robot motion for better hole quality, this paper proposes an optimization framework to eliminate or minimize joint reversals throughout a drilling motion. A general robotic drilling motion with a redundant degree of freedom due to the twist of the tool is first modeled. Particle Swarm Optimization (PSO) is then used for strategic pose selection considering the entire drilling motion. Experimental tests performed on a KUKA KR 6 R700-2 show a 40% reduction in the tool deviation envelope. The proposed technique can be readily implemented on any commercial robotic drilling cell without interfering with the controller.
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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