Automated End-Effector Alignment in Robotic Micromanipulation
Why this work is in the frame
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Bibliographic record
Abstract
Proper alignment of the end-effector is a critical procedure that determines the success of micromanipulation, such as robotic cell manipulation. Presently, end-effector alignment is performed manually and suffers from large misalignment error and inconsistency. Manual alignment often undesirably moves the end-effector (e.g., a glass micropipette) out of the limited field of view under microscopy and risks breaking the fragile end-effector. This article presents automated end-effector alignment in robotic micromanipulation. A rotational degree of freedom was added to a standard micromanipulator with translational degrees of freedom. The kinematic model of end-effector’s rotation was established, and the unknown model parameters were calibrated. To accommodate model uncertainty and parameter variations, a sliding mode controller was designed to achieve end-effector alignment. Experimental results demonstrate that the robotic alignment technique achieved an accuracy of 0.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm 0.3^{\circ }$</tex-math></inline-formula> and a time cost of 17.9 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 7.3 s, both significantly less than manual alignment. The developed controller based on kinematic modeling and sliding mode control achieved a higher success rate and significantly less time cost for end-effector alignment than the PID controller. Standard micropipettes were used as the end-effectors for sperm immobilization and oocyte penetration, important procedures in cell surgeries. The success rate of sperm immobilization was 98% by robotic micropipette alignment, higher than the success rate of 90% by manual alignment. Oocyte deformation before penetration was 28.1 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 7.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> m by robotic end-effector alignment, significantly less than the deformation of 54.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 13.2 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> m by manual alignment.
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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 | 0.001 |
| 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