Natural Human–Machine Interface With Gesture Tracking and Cartesian Platform for Contactless Electromagnetic Force Feedback
Bibliographic record
Abstract
In this article, a novel human-machine interface, in which two Leap Motion (LM) controllers and a coil are attached to a Cartesian platform to provide contactless electromagnetic force feedback for enhancing the accuracy and efficiency of human-robot manipulation tasks is presented. To implement such an interface, an interval Kalman filter, an improved particle filter, and a mean filter are integrated to estimate accurately the position and orientation of the hand gesture tracked by the two LM controllers, and to smoothen the movement of the Cartesian platform. The back propagation neural network is employed to regulate the electric currents of the coil attached to the Cartesian platform for accurate force feedback. A series of comparative experiments are performed, and the results show that the presented interface greatly improved the efficiency and accuracy of human-robot manipulation tasks in comparison with existing methods, indicating its great potentials for many industry scenarios.
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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 | 0.000 |
| 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 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".