Adaptive Force Tracking Control of a Magnetically Navigated Microrobot in Uncertain Environment
Why this work is in the frame
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Bibliographic record
Abstract
Magnetic navigation microrobotics is a promising technology in micromanipulation and medical applications. A magnetically navigated microrobot (MNM) usually has permanent magnets or ferromagnetic materials attached to it to create interaction force for navigation in the presence of an external magnetic field. During the exploration of the MNM, it is necessary to simultaneously control the position of the MNM and the contact force when the microrobot is constrained by its environment. However, owing to the small size of an MNM and noncontact property of magnetic levitation, installing on-board force sensors is very challenging. This paper presents a dual-axial interaction force determination mechanism that uses magnetic flux measurement, with no need for a conventional on-board force sensor. The interaction force is then used as the feedback force of a position-based impedance controller to actively track the reference force on the MNM in uncertain environment. To reduce the force tracking error caused by environmental uncertainty, an adaptive control algorithm is implemented to generate a reference motion trajectory that attempts to minimize the force error to an acceptable level. The force tracking performance of the robot is experimentally validated. A 2.01 μN root mean square force tracking error is reported. The proposed technique can be applied to biomedical microsurgery, such as for cutting tissue with controlled force.
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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