Position Control of a Magnetically Levitated Robot Based on Magnetic Flux Measurement
Bibliographic record
Abstract
Magnetic actuation has opened a new horizon in biological/biomedical applications. A novel magnetic actuation platform has been developed at Maglev Microrobotics Laboratory, University of Waterloo. In the previous work, laser sensors were used for positioning the levitated microrobot. This technique can be used only in transparent environment. In this paper, for applications in an enclosed environment, which may not be transparent, a novel position estimation method was proposed. The proposed method uses hall sensors, mounted on the disk pole-piece. The hall sensors’ optimal installation position has been investigated, and a function which relates hall sensors’ output and the position of robot was derived. Based on this function, position control of horizontal axis using hall sensors in place of laser sensor can be achieved. Usability of two dimensional controls in horizontal axis without laser sensors will be experimentally validated as future work of this research.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".